RAPID ASSESSMENT OF AVOIDABLE BLINDNESS AND DIABETIC RETINOPATHY REPORTPapua New Guinea 2017

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RAPID ASSESSMENT OF AVOIDABLE BLINDNESS AND DIABETIC RETINOPATHY

PAPUA NEW GUINEA, 2017

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Acknowledgements

The Rapid Assessment of Avoidable Blindness (RAAB) + Diabetic Retinopathy (DR) was a Brien Holden Vision Institute (the Institute) project, conducted in cooperation with the Institute’s partner in Papua New Guinea (PNG) – PNG Eye Care. We would like to sincerely thank the Fred Hollows Foundation, Australia for providing project funding, PNG Eye Care for managing the field work logistics, Fred Hollows New Zealand for providing expertise to the steering committee, Dr Hans Limburg and Dr Ana Cama for providing the RAAB training. We also wish to acknowledge the National Prevention of Blindness Committee in PNG and the following individuals for their tremendous contributions:

Dr Jambi Garap – President of National Prevention of Blindness Committee PNG, Board President of PNG Eye Care Dr Simon Melengas – Chief Ophthalmologist PNG Dr Geoffrey Wabulembo - Paediatric ophthalmologist, University of PNG and CBM Mr Samuel Koim – General Manager, PNG Eye Care Dr Georgia Guldan – Professor of Public Health, Acting Head of Division of Public Health, School of Medical and Health Services, University of PNG Dr Apisai Kerek – Ophthalmologist, Port Moresby General Hospital Dr Robert Ko – Ophthalmologist, Port Moresby General Hospital Dr David Pahau – Ophthalmologist, Boram General Hospital Dr Waimbe Wahamu – Ophthalmologist, Mt Hagen Hospital Ms Theresa Gende - Health Extension Officer, National Department of Health and Lecturer, Divine Word University Ms Schola Kapou – Nurse, Mendi General Hospital Mr Russell Kama – Student investigator, University of PNG Mr Bartholomew Kapakeu - Student investigator, University of PNG Ms Appolonia Parihuasi - Student investigator, University of PNG Mr Ishmael Robert – Student investigator, University of PNG Mr Kua Yarawo – Student investigator, University of PNG Mr Chris Paison – Ophthalmic clinician, Alotau Provincial Hospital Ms Stephanie Koriapi – Health Extension Worker with Boram General Hospital Mr Loamin Ikilik – Nurse, Nonga General Hospital Ms Anita John – Refractionist, PNG Eye Care Mr Jonah Jerry – Eye Nursing Officer, Port Moresby General Hospital Last, but not least, this research could not have been possible without the participants. We thank them for their cooperation and contribution to this research.

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Table of Contents

Acknowledgements .................................................................................................................... 2

List of Figures ............................................................................................................................. 4

List of Tables .............................................................................................................................. 5

Glossary of Terms ...................................................................................................................... 6

List of Abbreviations .................................................................................................................. 7

Key Messages ............................................................................................................................. 8

Executive Summary .................................................................................................................. 10

Introduction ............................................................................................................................. 14

1.1 The current eye care and diabetes situation in Papua New Guinea ......................... 14

1.2 Justification of the research ...................................................................................... 15

Research design and methodology .......................................................................................... 15

1.3 Objectives .................................................................................................................. 15

1.4 Protocol design .......................................................................................................... 15

1.4.1 RAAB Survey – Determining visual acuity and cause of blindness .................... 16

1.4.2 Local Modifications to RAAB form ..................................................................... 16

1.4.3 Diabetes and DR component ............................................................................. 16

1.4.4 Survey teams ...................................................................................................... 17

1.5 Sample size calculation and sampling ....................................................................... 17

1.6 RAAB training and quality control ............................................................................. 19

1.7 Ethical considerations ............................................................................................... 19

1.8 Data management and analysis ................................................................................ 19

1.8.1 Sample versus general population..................................................................... 20

1.8.2 National estimation of prevalence data ............................................................ 20

1.8.3 Regional estimations .......................................................................................... 20

1.8.4 Sex comparisons ................................................................................................ 20

Results ...................................................................................................................................... 21

1.9 Response rate ............................................................................................................ 21

1.10 Prevalence of blindness and vision impairment – sample population ..................... 21

1.11 Prevalence of blindness and vision impairment – age- and sex-adjusted ................ 22

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1.12 Causes of blindness and vision impairment – sample population ............................ 23

1.13 Cataract ..................................................................................................................... 24

1.13.1 Cataract prevalence ........................................................................................... 24

1.13.2 Cataract surgical coverage (CSC) ....................................................................... 25

1.13.3 Cataract surgery outcomes ................................................................................ 26

1.13.4 Barriers to accessing surgery ............................................................................. 26

1.14 Refractive error and spectacle coverage .................................................................. 28

1.15 Diabetes and DR in National Capital District ............................................................. 29

Discussion................................................................................................................................. 31

Project Learnings...................................................................................................................... 33

1.16 Training ...................................................................................................................... 33

1.17 Logistics and study procedures ................................................................................. 33

1.18 Data collection tools – mobile phones versus paper ................................................ 34

1.19 Other strengths and limitations ................................................................................ 35

Conclusion ................................................................................................................................ 36

References ............................................................................................................................... 37

Appendix 1 – Additional results ............................................................................................... 39

Appendix 2 – Project Contributors .......................................................................................... 46

Appendix 3 – Randomly Selected Clusters .............................................................................. 48

Appendix 4 – Regional Reports ................................................................................................ 53

List of Figures

Figure 1: Location of RAAB clusters in National Capital District (green), Coastal (red), Highlands (blue) and Islands (yellow) region ................................................................................ 18

Figure 2: Location of RAAB clusters in NCD Region ................................................................. 18

Figure 3 Reported barriers to cataract surgery by sex ............................................................ 27

Figure 4 Reported barriers to cataract surgery by region ....................................................... 27

Figure 5 Proportion of participants with known diabetes and last eye examination for DR .. 30

Figure 6 Sample prevalence of DR in National Capital District ................................................ 30

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List of Tables

Table 1 Sample size and coverage of the regions in Papua New Guinea ................................ 21

Table 2 Sample prevalence of blindness and visual impairment in Papua New Guinea - By eyes and individuals with available correction .................................................................... 22

Table 3 Age- and sex- adjusted prevalence of blindness and visual impairment in individuals and eyes with available correction in Papua New Guinea........................................... 23

Table 4 Principal causes of blindness and visual impairment in individuals in Papua New Guinea .......................................................................................................................... 24

Table 5 Age- and sex-adjusted prevalence of individuals with bilateral cataracts and total cataract eyes in Papua New Guinea - with best-corrected or pinhole visual acuity ... 25

Table 6 Cataract surgery coverage as a percentage of individuals and eyes .......................... 26

Table 7 Cataract surgical outcomes in Papua New Guinea - by presenting visual acuity (PVA) and best-corrected visual acuity (BCVA) ...................................................................... 28

Table 8 Prevalence of refractive error and uncorrected presbyopia of the sample population in Papua New Guinea ................................................................................................... 29

Table 9 Types of diabetes treatment reported in people with known diabetes ..................... 29

Table 10 Age and sex distribution of survey region and sample population in Papua New Guinea(2) ...................................................................................................................... 39

Table 11 Sample prevalence of blindness and visual impairment in the four regions of Papua New Guinea - By eyes and individuals with available correction ................................ 40

Table 12 Principal causes of blindness and visual impairment of individuals in the four regions of Papua New Guinea ................................................................................................... 41

Table 13 Age- and sex-adjusted prevalence of blindness and visual impairment in individuals and eyes with available correction in the four regions of Papua New Guinea ........... 42

Table 14 Age- and sex-adjusted prevalence of individuals with bilateral cataracts and total cataract eyes in Papua New Guinea - with best corrected or pinhole visual acuity ... 43

Table 15 Cataract surgical coverage (unadjusted) as a percentage of individuals and eyes in the four regions of Papua New Guinea ........................................................................ 44

Table 16 Cataract surgical outcomes in the four regions of Papua New Guinea – by presenting (PVA) and best-corrected visual acuity (BCVA) ............................................................ 45

Table 17 Prevalence of refractive error of the sample population in the four regions of Papua New Guinea .................................................................................................................. 45

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Glossary of Terms

Aphakia – The absence of the lens in the eye

Blindness – Visual acuity < 3/60 in the better eye with available or best correction or with pinhole. Definition provided by World Health Organization International Classification of Diseases – version 10. Visual fields are not taken into account in this report.

Early vision impairment (EVI) – Visual acuity < 6/12 – 6/18 in the better eye with available or best correction or with pinhole. Definition provided by Rapid Assessment of Avoidable Blindness Manual – version 6.

Moderate vision impairment (MVI) – Visual acuity < 6/18 – 6/60 in the better eye with available or best correction or with pinhole. Definition provided by World Health Organization International Classification of Diseases – version 10. Visual fields are not taken into account in this report.

Pseudophakia – The presence of an artificial lens in the eye

Severe vision impairment (SVI) – Visual acuity < 6/60 – 3/60 in the better eye with available or best correction or with pinhole. Definition provided by World Health Organization International Classification of Diseases – version 10. Visual fields are not taken into account in this report.

Visual acuity – The capacity of the eye to resolve detail and often represented as a fraction. The numerator of the fraction indicates the testing distance, while the denominator indicates the smallest letter that can be seen by someone with ‘normal’ vision.

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List of Abbreviations

95% CI 95% confidence interval AMD Age-related macular degeneration BCVA Best corrected visual acuity CSC Cataract surgical coverage DR Diabetic retinopathy EVI Early vision impairment IOL Intraocular lens MVI Moderate vision impairment NCD National Capital District PNG Papua New Guinea PVA Presenting visual acuity RAAB Rapid assessment of avoidable blindness RBG Random blood glucose SVI Severe vision impairment VA Visual acuity

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Key Messages

National prevalence of blindness and vision impairment (VI): • The estimated national prevalence (age-sex adjusted) of blindness, SVI, MVI and EVI in

adults aged 50 years and older in PNG is 5.6% (95%CI 4.9 – 6.3%), 2.9% (95%CI 2.5 – 3.4%), 10.9% (95%CI 9.9 – 11.9%) and 7.3% (95%CI 6.6 – 8.0%), respectively.

• Prevalence (age-sex adjusted) of blindness in adults aged 50 and older is significantly higher in females (7.0%, 95%CI 6.2 – 7.8%) compared to males (4.4%, 95%CI 3.4 – 5.4%)

• Prevalence of blindness is highest in females in the Highlands (11.1%, 95%CI 8.1 – 14.0%) and lowest in males in the Islands (0.7%, 95%CI 0.0 – 1.7%)

Causes of blindness and VI nationally: • Untreated cataract is the most common primary cause of blindness, SVI and MVI

(88.6% of all blindness, 89.3% of all SVI, 76.2% of all MVI) • Refractive error is the most common cause of EVI (45.3%) and the second most

common cause of MVI (16.1%)

Cataract surgical coverage (CSC) and outcomes: • National CSC (VA<6/60) is 32.3%, compared to the global median of 53.7% (based on

available RAAB repository data). • Lowest CSC in individuals is in the Highlands (females 9.2%, males 25.0%, p=0.02) • Highest CSC in individuals is in the Islands (females 46.7% female, males 78.3%, p=0.35) • Nationally, 61.3% of cataract operated eyes have good outcomes (BCVA ≥6/18) – WHO

recommend postoperative outcomes to have BCVA ≥6/18 in ≥90% operated eyes. • Increasing human resources and having biometry at all surgical locations may assist in

increasing CSC and improving outcomes.

Barriers to cataract surgery: • The most commonly reported barriers to cataract surgery are ‘unaware treatment is

possible’, ‘need not felt’ and ‘cost’. • Although not significant (p>0.05), ‘unaware treatment is possible’ and ‘need not felt’

are reported proportionally more by females compared to males in all regions and more commonly reported in all regions excluding Coastal.

• Cost is the most notable barrier for males in the Coastal region • Health education and increasing affordability could improve CSC and uptake.

Spectacle coverage: • 72.7% of participants with distance refractive error do not have correction (females

79.1%, males 61.3%, p<0.001); approximately 80% of participants do not have near correction (females 86.4%, males 79.3%, p>0.05)

• Increasing access to refractive services and spectacles are required in all regions, in particular for females.

Diabetes and diabetic retinopathy (DR): • Prevalence of diabetes* (age-sex adjusted) is estimated to be 8.1% (95%CI 5.7 – 10.4%)

in adults aged 50 years and older in NCD, which is lower than expected • Almost half (46.4%) of those with diabetes have some form of DR and or maculopathy • Over 80% of those with known diabetes have never had an eye examination for DR

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• These outcomes highlight the need for increased awareness in diabetes and eye health, and working together with other diabetes health professionals.

Blindness indicates VA <3/60; Severe vision impairment (SVI) indicates VA <6/60 but ≥3/60; Moderate vision impairment (MVI) indicates VA <6/18 but ≥6/60; Early vision impairment (EVI) indicates VA <6/12 but ≥6/18 *A previous diagnosis of diabetes or having had a random blood glucose reading of ≥200mg/dL

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Executive Summary

Background: Vision impairment and blindness are health concerns both globally, and in Papua New Guinea (PNG). Due to the absence of any population data related to vision impairment and blindness in the last decade in PNG, and considering the objectives of the WHO Global Action Plan towards Universal Eye Health, new estimates are required to advocate for the development of appropriate intervention programs.

A Rapid Assessment of Avoidable Blindness survey (RAAB) is intended to provide the prevalence of blindness and vision impairment, its main causes, cataract surgical coverage (CSC), cataract surgery outcomes, barriers to accessing services, and other indicators of eye care services in a specific geographical area. Recently, the standard RAAB protocol has been updated to include an optional module for assessing diabetes and diabetic retinopathy (DR). Non-communicable diseases such as diabetes, pose an increasing threat in PNG, as the burden of diabetes is now significant in urban areas. This study assessed the prevalence and main causes of blindness and vision impairment in people aged 50 years and older in four regions that make up PNG, as well as the prevalence of diabetes and DR in adults aged 50 years and older in the National Capital District (NCD) – the most urbanized and populated area in PNG.

The aim of this project is to contribute to the development of eye care services in PNG through gathering evidence on the prevalence of avoidable blindness and vision impairment in all four regions in PNG, and the prevalence of DR in the NCD.

Methods: This was a cross-sectional population-based survey completed in all regions of PNG. With appropriate local guidance, it was decided that four RAAB surveys be conducted at the regional level, as each of the four regions in PNG was likely to portray different patterns of vision impairment, and comparison at the regional level was desirable. The regions were the Highlands (all provinces within the administrative region, Islands (all provinces within the administrative region and Milne Bay Province), Coastal (Momase and Papua administrative regions combined but excluding Milne Bay Province) and NCD. In addition, the increasing prevalence of diabetes particularly in the urban areas prompted the inclusion of the DR module with the RAAB in the NCD. Inclusion criteria were adults aged 50 or above who had resided in the household within the selected cluster sampling unit for a minimum of 6 months.

Twenty-five clusters (census units) were systematically selected with a probability proportional to the size of each cluster in each of the four regions. Within each cluster, 50 people aged 50 years or older were recruited. The study protocol was conducted according to the standard RAAB protocol. Where appropriate, the survey form was modified to reflect the PNG local environment. For example, onchocerciasis was replaced with Eales disease, as the former was not found in PNG.

In NCD, participants additionally underwent a random blood glucose (RBG) test and were classified as having diabetes if they were previously diagnosed with diabetes, were receiving

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treatment for glucose control, or if they were found to have a RBG level of ≥200 mg/dL (equivalent to ≥11.1 mmol/L) at the time of data collection. Those with a previous diagnosis were surveyed on past eye examinations. For those classified with diabetes, a dilated fundus examination was conducted to assess presence of DR.

Data cleaning, consistency checks and analysis were conducted with RAAB6 Software (Version 6, London School of Hygiene & Tropical Medicine, UK) and SPSS Statistical software (IBM, Version 24.0, USA)

Results: Of the 5,000 eligible participants sampled from the four regions of PNG, a total of 4,818 participants (96.4%) consented to the eye examination and survey. Overall, the PNG-wide predicted age- and sex-standardised prevalence of blindness was 5.6% (95% CI 4.9 – 6.3%), with a significantly greater proportion of females being blind (7.0%, 95% CI 6.2 – 7.8%) compared to males (4.4%, 95%CI 3.4 – 5.4%). Regionally, the prevalence of blindness was highest in females in the Highlands (11.1%, 95%CI 8.1 – 14.0%) and lowest in males in the Islands (0.7%, 95%CI 0.0 – 1.7%).

For all regions, untreated cataract was the most common cause of blindness (81.8% in NCD, 90.4% in the Highlands, 91.0% in Coastal, and 81.0% in Islands), severe (77.8% in NCD, 95.7% in Highlands, 90.7% in Coastal, and 73.3% in Islands), and moderate vision impairment (58.9% in NCD, 89.3% in Highlands, 76.6% in Coastal and 62.1% in Islands). Refractive error was observed to be the main cause of early vision impairment (58.3% in NCD, 13.5% in Highlands, 41.1% in Coastal and 70.6% in Islands). Across all regions, as the level of vision impairment became less severe, an increasing proportion of vision impairment was due to refractive error rather than untreated cataract. Other posterior segment eye diseases leading to reduced visual acuity (VA) were the second most common cause of blindness nationally (3.9%). Age-related macular degeneration (AMD) associated with early vision impairment was most commonly seen in the Islands region (80% of those with AMD as the primary cause of early vision impairment were from the Islands region). Trachomatous corneal opacity leading to bilateral blindness was only seen in one participant in the Islands. No occurrences of presenting VA of <6/12 where the primary cause was due to uncorrected aphakia, Eales’ disease or glaucoma were observed.

After adjusting for age and sex, a significantly greater prevalence of cataracts resulting in VA <3/60 was observed in females (9.2%, 95%CI 8.4 – 10.0) compared to males (6.2%, 95%CI 5.3 – 7.2). However, the difference between sexes was only statistically significant in the Highlands, based on comparing 95% confidence intervals for overlap between sexes for each region (male 8.6%, 95%CI 6.0 – 11.1%; female 14.6%, 95%CI 11.2 – 18.0%).

The national weighted average for CSC was 32.3% (VA<6/60), but ranged from 9.2% (females in the Highlands) to 78.3% (males in the Islands). Males had better CSC (VA<6/60) in the Highlands (25% versus 9.2%, p=0.04). When comparing regions, the Islands (65.8%) had highest coverage followed by NCD (35.9%), Coastal (32.6%) and the Highlands (18.1%).

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Just over 60% of the participants’ eyes that have had cataract surgery have resulted in a good visual outcome (best-corrected VA≥6/18). However, 25.1% of operated eyes have resulted in a very poor visual outcome (best-corrected VA<6/60).

No statistically significant difference in reasons for not accessing cataract surgery services were observed between genders, however females reported ‘unaware [cataract] treatment is possible’ more commonly than males (33.6% versus 26.7%). ‘Need not felt’ for cataract surgery was a commonly reported response for both sexes in all regions (NCD: 42.4%; Highlands: 38.1%; Islands: 33.3%;) except the Coastal region (16.3%). Cost was considered the most prominent barrier to cataract surgery in the Coastal region (35.0%). Fear of surgery was not reported as a barrier to cataract surgery in the Highlands, however a notable proportion reported ‘need not felt’ or ‘unaware treatment is possible’ as the main barriers (38.1% and 42.6%, respectively). ‘Cannot access treatment’ was reported by participants in all regions other than NCD. No reports of treatment denial or ‘local beliefs’, which pertain to local cultural fears such as a fear of sorcery were provided as reasons for not accessing cataract surgery services.

The prevalence of distance refractive error was estimated to be 8.2% in adults aged 50 years and above. The lowest spectacle coverage was found in females in the Highlands (distance spectacles: 5.3%; near spectacles: 2.9%) and the Islands (distance spectacles: 19.6%, near spectacles: 29.5%) regions. For males and females with distance refractive error, 65.7% and 71.2% were uncorrected, respectively. For presbyopia, spectacle coverage was 17.5% of the sample population.

In our sample, 7.8% (95%CI 5.5-10.1%) of adults aged 50 years and above were defined as having diabetes. After adjusting for age and sex, the estimated prevalence of diabetes in the NCD was 8.1% (95%CI 5.7-10.4%) in adults aged 50 years and above. Of those with diabetes, 62.4% were ‘newly-diagnosed’ (reported that he/she did not have diabetes, but RBG level was ≥200mg/dL) and 37.6% had a previous diagnosis. Of the 35 participants with known diabetes, 71.4% had poor control of their blood sugar levels (indicated by RBG ≥200mg/dL). Over 80% of participants with known diabetes reported never having had an eye examination for DR, while only 11.4% had an eye examination within the last 12 months. Of all participants with diabetes (known and newly-diagnosed), almost half (46.4%) had some form of DR or maculopathy.

Discussion: This was the first national survey of vision impairment and blindness to have been conducted in PNG. The estimated prevalence of blindness in people aged 50 years and older in PNG was 5.6% (95% CI 4.9 – 6.3%) and although not statistically significant, was higher than the previous estimation of 3.9% (95%CI 3.4 – 6.1%) in Koki and Rigo. Considering the different surveyed areas, comparisons are to be taken with caution.

The primary cause of vision impairment in PNG was untreated cataract. Burden of disease was high across all regions, but particularly in the Highlands region, and especially for females. Based on current WHO recommendation, PNG is below the recommended target that at least

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90% of people who had cataract surgery should have postoperative best-corrected VA of 6/18 or better and at most 5% postoperative best-corrected VA worse than 6/60. However, based on available RAAB data from other countries, these recommended rates have yet to be achieved elsewhere in the region, or in fact globally. While developing approaches to improve cataract surgery outcomes in PNG are essential, we have identified that there is also a need to provide eye health education to the older population on the availability and potential benefits of cataract surgery. In addition, education to improve attitudes towards spectacles may be required, as spectacle presentation was relatively low in general, but particularly for females and for those in the Highlands region.

The diabetes prevalence in adults aged 50 years and older was lower than previous reports in NCD (8.1% versus 14.4%). The difference in reports might be due to the fact that different methods were employed to diagnose diabetes; assessment in this study was based on a single RBG test and diagnostic criteria of ≥200mg/dL. The rates of adults aged 50 year or older who were newly diagnosed based on this test was high (62.4%), and almost half of those with diabetes had some form of DR or maculopathy; this indicates that undiagnosed diabetes and DR are likely to be increasingly significant public health issues in PNG with increasing rates of diabetes. As we detected low levels of awareness and previous treatment for diabetes and DR in this NCD population, better education, and prevention services for early detection, prevention and treatment will be required. Importantly, those with diabetes will need specific awareness messages about the risk of visual loss from DR. Developing and evaluating a comprehensive model of eye care, which includes eye care services for people with diabetes will be important next steps for improving the eye health of people in PNG.

Achieving equitable access to eye care services for both males and females and those from remote areas will be a long-term goal in PNG. Ongoing advocacy to increase services and improve services and support, particularly for women and those from rural areas, to engage with eye care services is required to reduce the inequities in eye health that exist in PNG.

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Introduction

Vision impairment and blindness are worldwide health concerns affecting approximately 401 million and 36 million respectively; (1)the most affected communities and countries are those with limited resources and poor accessibility to services. Papua New Guinea (PNG) is the largest and most populous country in the South Pacific with a population of over seven million.(2) PNG is a geographically and socio-demographically diverse country divided into 19 provinces and with over 800 distinctive, mutually unintelligible languages, each representing a distinct culture.(2, 3) An estimated 87% of the population lives in rural areas and is partially or substantially living a subsistence lifestyle.(4) Administratively, PNG is divided into 22 province-level divisions spread across four regions: Highlands, Islands, Momase, and Papua region.

1.1 The current eye care and diabetes situation in Papua New Guinea Currently, there are approximately 14 practicing ophthalmologists, two primary eye care ophthalmologists, five ophthalmologists in training, five optometrists in private practice, seven refractionists, and 67 ophthalmic clinicians across PNG. The majority of eye health clinics are located in Port Moresby, the country’s capital, and in the provincial capitals including Mendi, Mt Hagen, Goroka, Lae, Madang, Wewak, Rabaul and Kimbe. However, outreach services are provided across some regions on an ad-hoc basis.

The most recent vision related epidemiological eye study was conducted over 10 years ago (2004-2005) and established that PNG has high rates of vision impairment (29%) and blindness (3.9) in older adults. Uncorrected refractive error and cataract were reported as the two most common causes of vision impairment in people aged 50 years and older.(5) This survey, however, was only conducted in one rural and one urban sample in the proximity of Port Moresby.

Adults living in rural PNG have reported expensive travel costs to be a notable barrier to attending clinics.(6) Therefore, exploring the prevalence of blindness and vision impairment across the whole country can assist in planning where to develop eye care services to improve access.

The World Health Organization (WHO) has estimated that the prevalence of diabetes in PNG is approximately 11.8%, almost equal between genders, and appears to be increasing.(7) It has been suggested diabetes tends to be more prevalent in urban and coastal areas and that it is associated with westernisation.(8, 9) Despite diabetes in the PNG population being investigated since the 1960s, the most recent epidemiological study was conducted in 2008, and found that 14.7% of males and 14.4% of females had elevated blood glucose levels or were currently on medication for diabetes.(10)

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1.2 Justification of the research One of the WHO Global Action Plan objectives for Universal Eye Health is “generating evidence on the magnitude and causes of vision impairment and eye care services”.(11) The previous survey of blindness and vision impairment in PNG was only conducted in areas within and surrounding Port Moresby, PNG’s capital. Due to the absence of any population data related to vision impairment and blindness in at least the last decade, new estimates are required to advocate for the development of appropriate intervention programs.

Surveys assessing blindness and vision impairment have previously been avoided due to perception that they involve lengthy, costly, and complex processes, and that they require expert assistance from epidemiologists or statisticians to produce reports. The Rapid Assessment of Avoidable Blindness survey (RAAB) methodology was developed to address these challenges. The RAAB provides evidence on the prevalence of blindness and vision impairment, their main causes, cataract surgical coverage (CSC), cataract surgery outcomes, barriers to accessing cataract services, and other eye health indicators in a specific geographical area. Recently, the standard RAAB protocol has been updated to include an optional module for assessing diabetes and diabetic retinopathy (DR). Taking into consideration the concerning issue of the increasing prevalence of diabetes, particularly in urban areas, assessing the prevalence of DR is vital to planning eye care services and eye health education in PNG.

The aim of this project is to contribute to the development of eye care services in PNG through gathering evidence on the prevalence of avoidable blindness and vision impairment in all four regions in PNG, and the prevalence of DR in the National Capital District (NCD).

Research design and methodology

1.3 Objectives • To determine the prevalence and main causes of blindness and vision impairment in

people aged 50 years and older in four regions of PNG. • To determine the CSC, surgery outcomes, and barriers to accessing services in people

aged 50 years and older in all regions of PNG. • To determine the prevalence of diabetes and DR in people aged 50 years and older in

the NCD region of PNG

1.4 Protocol design This was a cross-sectional population-based survey completed in all regions of PNG. With appropriate local guidance, it was decided that four RAAB surveys be conducted at the regional level which would all contribute to national data. The four regions are: Highlands, Islands (including Milne Bay Province), Coastal (Momase and Papua combined but excluding Milne Bay Province) and National Capital District (NCD). As it was felt that regions in PNG portrayed different patterns of vision impairment, comparison at regional level was desirable.

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In addition, because of the increasing prevalence of diabetes particularly in the urban areas, the DR module was included in the RAAB only in the NCD.

In order to be able to have sufficient sample size to estimate ‘blindness’ in each region, four separate RAAB surveys would have been required, each with a sample of approximately 4000 participants. As a compromise, based on available personnel and funding, the protocol was designed to estimate the level of both blindness and vision impairment nationally, but to also have the sample sufficiently powered in each region to estimate and compare the prevalence of ‘vision impairment’.

Inclusion criteria were adults aged 50 years or older who had resided in the household within the cluster for a minimum of six months.

1.4.1 RAAB Survey – Determining visual acuity and cause of blindness

All participants were interviewed on whether any problems were experienced with their eyes, whether spectacles (distance and near) were used, and education level. Presenting visual acuity (VA) was then checked in broad daylight. Pinhole VA was checked if the eye had presenting VA <6/12. All participants were directed into a shaded area or indoors for lens examination with direct ophthalmoscopy. If pinhole VA was <6/12, the participant’s pupils were dilated with tropicamide 0.5% solution and direct ophthalmoscopy was performed to determine the cause of reduced vision for each eye. The overall primary cause of VA <6/12 was determined to be the cause that was most easily treatable. For example, if one eye had vision impairment due to refractive error, while the other had reduced VA due to significant cataract, refractive error was chosen to be the overall primary cause. Should the participant be noted to have had or in need of cataract surgery, details of the surgery or reasons for not having had surgery done were surveyed. Participants identified as requiring further eye care were referred to appropriate services.

1.4.2 Local Modifications to RAAB form

During the training program, it was noted that onchocerciasis is not present in PNG – it was decided to replace onchocerciases on the record survey with Eales disease, as there were reports of significant cases. For barriers to cataract surgery, the field ‘local beliefs’ was included to capture specific local beliefs around the fear or sorcery.

1.4.3 Diabetes and DR component

All participants in NCD were invited to undergo a diabetes assessment, which involved asking whether they had previously been diagnosed with the disease and having a random blood glucose (RBG) test (finger prick). Those determined as having diabetes were also surveyed on the type of treatment (if any) they were receiving for the disease, when first diagnosis was made, and whether an eye examination had been conducted since being diagnosed with diabetes.

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Participants determined as being ‘newly-diagnosed’ with diabetes were those who reported not being previously diagnosed and had a RBG level ≥200mg/dL. All known and newly-diagnosed diabetes participants had their pupils dilated with 0.5% tropicamide solution for a DR assessment. The Scottish Diabetic Retinopathy Grading Scheme was used to record and grade the observations. All participants with elevated RBG levels (whether known or newly diagnosed diabetes) and signs of DR were referred to the appropriate health facility for further management.

1.4.4 Survey teams

Five survey teams, two for the NCD region and one for each of the other regions, were formed to complete data collection. Each survey team consisted of an ophthalmologist, a research assistant/student co-investigator and local commune health worker. In the NCD region, an additional diabetes officer certified in DR grading accompanied the survey team to conduct diabetes and DR screenings.

1.5 Sample size calculation and sampling A total of 5,000 participants, with a sample of 1,250 persons within each of the four regions was required to estimate a prevalence of blindness at 3.9%(5) at a 95% confidence level, with relative precision of 20%, design effect of 1.5, and drop-out or refusal rate of 10%. For each region, 25 clusters (census units) were selected and 50 adults were recruited within each cluster.

Cluster sampling was applied to determine sampling areas. Four sampling frames were developed (one for each region), with each frame including the list of census units obtained from the National Statistical Office, PNG. This stage involved selecting 25 clusters systematically from the sampling frame with a probability according to their population size. This procedure is known to be self-weighing and also ensures that the selection of clusters is evenly spread over the entire population.(12) In clusters where less than 50 adults aged 50 years and older resided, examination continued in the geographically nearest population unit to complete the cluster. The distribution of clusters selected across PNG is shown in Figure 1 and Figure 2.

Survey teams went door-to-door to identify eligible participants. If eligible participant were identified, yet were not available at the time of visit, up to three attempts to arrange and contact them at the household were conducted. Should participants continue to not be available, a neighbour or relative willing to complete a portion of the survey were interviewed on the likely vision status of the eligible participant.

In some clusters, households members spontaneously self-presented to the teams when they arrived in a village. This is common practice in PNG when there are visiting health or research teams, and it was not considered acceptable to turn an entire village away. In these instances, in order to avoid selection bias, the survey teams enquired as to whether any other eligible

18

adults were living in a participant’s household. If so, these households were visited in order to appropriately sample all eligible adults in the cluster.

Figure 1: Location of RAAB clusters in National Capital District (green), Coastal (red), Highlands (blue) and Islands (yellow) region

Figure 2: Location of RAAB clusters in NCD Region

19

1.6 RAAB training and quality control Dr Hans Limburg, Dr Anthea Burnett, and Dr Ana Cama conducted training of data collectors in Port Moresby over a one-week period. Training included the provision of an overview of the RAAB protocol, discussions about logistics, and training to obtain informed consent from participants, examine participants’ eye health, record data, assess inter-observer agreement on VA measurement, and grade DR. Practical exercises and a village visit were conducted to ensure that the survey teams had hands-on experience in the field prior to commencement of data collection.

To maintain high quality data collection processes, additional activities and information were provided, including:

- A refresher quiz was provided to all survey team members prior to data collection - “Tips and Tricks” emails on noted deviations or misunderstandings from the protocol

were sent on a weekly basis to remind survey team members

1.7 Ethical considerations All participants were required to provide written or thumbprint consent to participate in the RAAB and, if in the NCD region, DR component. The study was approved by the Medical Research Advisory Committee of PNG (Ref. MRAC No.16.35) and The University of New South Wales Human Research Ethics Committee (Ref. HC16804). Additional ethics approval was obtained for data collection in Milne Bay Province through the Milne Bay Provincial Health Authority (Ref. DPA:3-15).

1.8 Data management and analysis For all regions excluding NCD, data were recorded on android mobile phones using the mRAAB application. Data from the mRAAB application were emailed to the research team, and then imported into the RAAB6 software (Version 6, London School of Hygiene & Tropical Medicine, UK), which is then used for data analyses. Due to the additional DR component, data collected in the NCD were recorded on paper survey forms and then entered into the RAAB6 software (the mRAAB app does not yet allow for the collection of DR data). The data were assessed regularly with the RAAB6 in-built consistency check. Any discrepancies identified were immediately reported back to the survey teams for clarification.

Data cleaning, and analysis was conducted with RAAB6 Software. For all four regions, the following reports were generated:

1) Summary report (Appendix 4) 2) Prevalence of blindness and vision impairment - unadjusted sample population 3) Prevalence of blindness and vision impairment – age- and sex-adjusted 4) Tables on prevalence of blindness and vision impairment by age groups and gender 5) Barriers to cataract surgery 6) Cataract surgical coverage and outcomes

20

7) Calculations on sampling error and design effect

For the NCD region, an additional report on diabetes and DR prevalence was generated with RAAB6 Software (Appendix 4).

Unadjusted calculations for uncorrected distance and near refractive error only included participants achieving presenting or pinhole VA of ≥6/12 to exclude those with vision impairment due to non-refractive causes.

1.8.1 Sample versus general population

Representativeness of the sample was evaluated by comparing the sample profile with the 2011 census regional and country population figures using the chi-squared test.

1.8.2 National estimation of prevalence data

Estimates of the national prevalence of blindness and vision impairment (at each VA level), CSC and uncorrected refractive error, were determined by calculating a weighted average, using census data for males and females aged 50 years or older in each region.

Where applicable, 95% confidence intervals (95%CIs) were calculated using the weighted average outcomes and corresponding standard errors (SEcrs) for cluster sampling. Standard errors were calculated by combining data from the four regions and generating the ‘Sampling Error and Design Effect’ report from the RAAB6 software.

1.8.3 Regional estimations

Regional data were generated by creating separate databases for each region in RAAB6 and generating the analysis reports. Differences in the regional estimates were determined by non-overlapping 95%CIs for the following variables: unadjusted prevalence of blindness, vision impairment and distance refractive error, as well as the adjusted prevalence of blindness, vision impairment and cataract.

1.8.4 Sex comparisons

Differences between males and females were assessed by overlapping 95% CIs or chi-square tests. Outcomes analysed by assessing 95%CIs included unadjusted prevalence of blindness, vision impairment and distance refractive error, as well as adjusted prevalence of blindness, vision impairment and cataract. Outcomes analysed with the chi-square test included unadjusted data of cataract surgical coverage and barriers to accessing surgery.

P values < 0.05 or no overlap of 95%CI were considered statistically significant.

21

Results

1.9 Response rate Of the 5,000 eligible participants sampled from the four regions of PNG, a total of 4,818 participants (96.4%) consented to the eye examination and survey. Table 1 shows the sample coverage in each region and Table 10 (Appendix 1) details the age and sex distribution of the surveyed region and sample population. A significantly greater proportion of older age groups (70-79 years and 80+ years) were in the sample in comparison to the population distribution (p < 0.001). This occurred in all regions except NCD where participants were predominantly in the 50-59 age group. In terms of gender, males were significantly overrepresented in the Highlands, whereas females were overrepresented in the NCD, compared to regional distributions (both p < 0.001).

Table 1 Sample size and coverage of the regions in Papua New Guinea Region Sample size Examined Coverage (%) National Capital District 1,250 1,192 95.4 Highlands 1,250 1,205 96.4 Coastal 1,250 1,242 99.4 Islands 1,250 1,179 94.3 Papua New Guinea (combined) 5,000 4,818 96.4

1.10 Prevalence of blindness and vision impairment – sample population Overall, 6.1% (95%CI 5.0 – 7.1%) of the sample population had bilateral blindness. Although not statistically significant, females (7.0%, 95%CI: 5.6 – 8.4%) appeared to have a greater prevalence of bilateral blindness compared to males (5.3%, 95%CI: 4.0 – 6.6%). A breakdown of the prevalence of blindness and severity of vision impairment by gender is presented in Table 2, with regional data presented in Appendix 1, Table 11.

22

Table 2 Sample prevalence of blindness and vision impairment in Papua New Guinea - By eyes and individuals with available correction

Papua New Guinea – Frequency and weighted average

Male Female Total n % (95%CI) n % (95%CI) n % (95%CI)

Blindnessa

Individuals* 106 5.3 (4.0-6.6) 119 7.0

(5.6-8.4) 225 6.1 (5.0-7.1)

Eyes 469 10.8 (9.6-12.0) 437 12.1

(11.1-13.1) 906 11.3 (10.4-12.3)

Severe vision impairmentb

Individuals 70 3.3 (2.3-4.4) 52 3.0

(1.9-4.0) 112 3.2 (2.4-3.9)

Eyes 209 4.7 (4.1-5.4) 141 3.7

(3.0-4.3) 350 4.3 (3.9-4.7)

Moderate vision impairmentc

Individuals 248 11.5 (10.0-13.1) 244 12.4

(10.2-14.6) 492 11.9 (10.5-13.3)

Eyes 537 12.1 (11.0-13.3) 528 12.9

(11.8-14.1) 1,101 12.6 (11.6-13.6)

Early vision impairmentd

Individuals 209 8.5 (7.2-9.8) 156 6.9

(5.5-8.3) 365 7.8 (6.7-8.8)

Eyes 463 9.4 (8.1-10.6) 360 7.6

(6.6-8.7) 823 8.6 (7.7-9.4)

*Data for individuals refers to bilateral cases; 95% CI = 95% confidence interval a Blindness: VA <3/60; b Severe vision impairment: VA <6/60 but ≥3/60; c Moderate vision impairment: VA <6/18 but ≥6/60, d Early vision impairment VA <6/12 but ≥6/18

Moderate vision impairment was the most commonly observed form of vision impairment, while severe vision impairment was the least observed. For blindness and each vision impairment severity, a statistically significant association of increasing prevalence was seen with increasing age (all p < 0.001, linear-by-linear association test).

1.11 Prevalence of blindness and vision impairment – age- and sex-adjusted Overall, as shown in Table 3, the predicted age- and sex-standardised prevalence of blindness was 5.6% (95%CI 4.9 – 6.3%) in PNG. Prevalence of blindness was significantly greater among females (7.0%, 95%CI 6.2 – 7.8%) than males (4.4%, 95%CI 3.4 – 5.4%). Regionally, prevalence of blindness was highest in females in the Highlands (11.1%, 95%CI 8.1 – 14.0) and lowest in males in the Islands (0.7%, 95%CI 0.0 – 1.7). A detailed breakdown of each region by gender is shown in Appendix 1, Table 13.

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Table 3 Age- and sex- adjusted prevalence of blindness and vision impairment in individuals and eyes with available correction in Papua New Guinea

Papua New Guinea – Frequency and weighted average

Male Female Total n % (95%CI) n % (95%CI) n % (95%CI)

Blindnessa

Individuals* 17,495 4.4 (3.4 - 5.4) 23,251 7.0

(6.2 - 7.8) 40,746 5.6 (4.9 - 6.3)

Eyes 76,740 9.6 (8.4 - 10.8) 77,945 11.8

(10.8 - 12.7) 154,685 10.6 (9.7 - 11.5)

Severe vision impairmentb

Individuals 11,858 3.0 (2.4 - 3.6) 9,661 2.9

(2.1 - 3.7) 21,519 2.9 (2.5 - 3.4)

Eyes 34,900 4.4 (3.8 - 5.0) 23,499 3.4

(2.9 - 4.2) 58,399 4.0 (3.6 - 4.4)

Moderate vision impairmentc

Individuals 40,670 10.2 (9.1 - 11.3) 38,793 11.7

(10.4 - 13.0) 79,463 10.9 (9.9 - 11.9)

Eyes 88,250 11.1 (9.9 - 12.2) 83,027 12.5

(11.2 - 13.8) 171,277 11.7 (10.7 - 12.7)

Early vision impairmentd

Individuals 31,455 7.9 (6.8 - 8.9) 21,679 6.5

(5.7 - 7.4) 53,134 7.3 (6.6 - 8.0)

Eyes 70,861 8.9 (7.7 - 10.1) 49,564 7.5

(6.5 - 8.5) 120,425 8.2 (7.4 - 9.1)

a Blindness indicates VA <3/60; b Severe vision impairment (SVI) indicates VA <6/60 but ≥3/60; c Moderate vision impairment (MVI) indicates VA <6/18 but ≥6/60; d Early vision impairment (EVI) indicates VA <6/12 but ≥6/18

1.12 Causes of blindness and vision impairment – sample population Table 4 presents the primary causes of blindness and vision impairment of participants nationally. The equivalent regional data is presented in Appendix 1, Table 12. For all regions, the most common cause of blindness, severe, and moderate vision impairment was untreated cataract. Refractive error was found to be the main cause of EVI. In all regions, as the severity of vision impairment reduced, the proportion of vision impairment due to untreated cataract also reduced. . Nationally, the second most common cause of blindness and reduced visual acuity was ‘other posterior segment eye diseases’. Age-related macular degeneration associated with early vision impairment was most commonly seen in the Islands region. Trachomatous corneal opacity leading to bilateral blindness was only seen in one participant in the Islands. There were no occurrences of presenting visual acuity of <6/12, where the primary cause was due to uncorrected aphakia, Eales’ disease, or glaucoma.

24

Table 4 Principal causes of blindness and vision impairment in individuals in Papua New Guinea

Primary Cause

Papua New Guinea, Frequency (weighted average, %)

Blindness, (n=225)

n (%)

SVI, (n=122)

n (%)

MVI, (n=492)

n (%)

EVI, (n=365)

n (%) Refractive error 0 (0.0) 2 (1.4) 92 (16.1) 190 (45.3) Cataract, untreated 199 (88.6) 108 (89.3) 360 (76.2) 130 (43.6) Cataract surgical complications 3 (1.1) 1 (1.2) 7 (1.4) 3 (1.5) Trachomatous corneal opacity 1 (0.8) 0 (0.0) 0 (0.0) 0 (0.0) Non-trachomatous corneal opacity

4 (2.1) 2 (1.7) 0 (0.0) 0 (0.0)

Phthisis 0 (0.0) 1 (1.0) 0 (0.0) 0 (0.0) Diabetic retinopathy 0 (0.0) 1 (1.2) 0 (0.0) 1 (0.2) Age-related macular degeneration

2 (0.5) 1 (1.2) 6 (1.5) 10 (2.0)

Other posterior segment disease 10 (3.9) 4 (1.5) 27 (4.8) 31 (7.4) All other globe/CNS abnormalities

6 (2.9) 2 (1.6) 0 (0.0) 0 (0.0)

NOTE: No occurrences of presenting visual acuity of <6/12 were the primary cause due to uncorrected aphakia, Eales’ disease or glaucoma

a Blindness indicates VA <3/60; b Severe vision impairment (SVI) indicates VA <6/60 but ≥3/60; c Moderate vision impairment (MVI) indicates VA <6/18 but ≥6/60; d Early vision impairment (EVI) indicates VA <6/12 but ≥6/18

1.13 Cataract

1.13.1 Cataract prevalence

Almost half of all eyes (48.4%; 4,662 eyes) were observed to have notable cataract resulting in visual acuity worse than 6/12. After adjusting for age and sex, a significantly greater prevalence of cataracts resulting in visual acuity worse than 3/60 was observed in females compared to males (Table 5). However, the difference between sexes was only statistically significant in the Highlands, based on comparing 95%CI for overlap between sexes for each region. The prevalence of cataract was significantly higher in the Highlands and Coastal regions for both genders compared to NCD and the Islands. A detailed breakdown on the age- and sex-adjusted prevalence of cataracts grouped by best-corrected visual acuity, gender and region is presented in Appendix 1, Table 14.

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Table 5 Age- and sex-adjusted prevalence of cataract (bilateral individuals and total cataract eyes) in Papua New Guinea - with best-corrected or pinhole visual acuity

Visual acuity

Papua New Guinea – Frequency and weighted average Male Female Total

n % (95%CI) n % (95%CI) n % (95%CI) < 3/60

Individuals 12,411 3.1 (2.4-3.9) 19,544 5.9

(5.3-6.5) 31,955 4.4 (3.8-4.9)

Eyes 49,845 6.2 (5.3-7.2) 60,922 9.2

(8.4-10.0) 110,767 7.6 (6.8-8.3)

< 6/60 – 3/60

Individuals 6,235 1.6 (1.1-2.0) 5,868 1.8

(1.1-2.4) 12,103 1.7 (1.3-2.0)

Eyes 20,588 2.6 (2.1-3.0) 14,292 2.2

(1.7-2.7) 34,880 2.4 (2.0-2.7)

< 6/18 – 6/60

Individuals 21,619 5.4 (4.6-6.2) 18,967 5.7

(4.6-6.9) 40,586 5.6 (4.7-6.4)

Eyes 53,032 6.6 (5.8-7.5) 43,058 6.5

(5.4-7.6) 96,090 6.6 (5.7-7.4)

< 6/12 – 6/18

Individuals 23,829 6.0 (5.1-6.8) 21,015 6.3

(5.6-7.1) 44,844 6.1 (5.5-6.8)

Eyes 55,072 6.9 (6.0-7.8) 44,926 6.8

(5.8-7.7) 99,998 6.8 (6.0-7.7)

1.13.2 Cataract surgical coverage (CSC)

Cataract surgical coverage is the proportion of individuals or eyes that have had cataract surgery (pseudophakia or aphakia) amongst individuals or eyes that have operable cataract for a specified level of visual acuity. Unadjusted average national coverage was 32.3% (VA<6/60, Table 6), but ranged from 9.2% (female in the Highlands) to 78.3% (males in the Islands) (Appendix 1, Table 15). When comparing regions, the Islands had significantly higher average CSC compared to all other regions (65.8% compared to 18.1 – 35.9%, p < 0.001). At all levels of VA, CSC for individuals was significantly lower in females compared to males in the Highlands. At all levels of VA, CSC of eyes was significantly lower in females compared to males in the Highlands and Islands, as well as in NCD but only for VA < 6/60 (all p<0.05).

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Table 6 Cataract surgery coverage as a percentage of individuals and eyes

Visual acuity Papua New Guinea, Weighted average

Male (%) Female (%) Total (%) < 3/60 Individuals 44.0 29.6 37.4 Eyes 33.5 19.7 27.3 < 6/60 Individuals 39.2 23.9 32.3 Eyes 28.2 16.2 22.8 < 6/18 Individuals 27.7 15.5 22.2 Eyes 18.1 10.2 14.7

1.13.3 Cataract surgery outcomes

Over 60% of the participants’ eyes (61.3%) that have had cataract surgery have resulted in a good visual outcome (VA>6/18) with best corrected visual acuity. However approximately one quarter of operated eyes have resulted in a very poor visual outcome (VA<6/60) (Table 7). Combined data for surgical outcomes across the country, as well as a breakdown outcome data for each region are presented in Appendix 1, Table 16.

Of those who had poor cataract surgical outcomes (VA<6/60), 53.3% had long-term complications such as posterior capsular opacification or retinal detachment, 28.3% had operative complications and 18.3% had ocular co-morbidities.

1.13.4 Barriers to accessing surgery

Barriers to cataract surgery were variable between sexes and regions and proportions are presented in Figure 3 and Figure 4. Although not statistically significantly different, ‘unaware [cataract] treatment is possible’ and ‘need not felt’ were reported proportionally more by females compared to males. The same two barriers were more commonly reported in all regions except the Coastal region. ‘Cost’ was considered the most prominent barrier to cataract surgery in the Coastal region. ‘Fear’ was not reported as a barrier to cataract surgery in the Highlands, however a notable proportion reported ‘need not felt’ or ‘unaware treatment is possible’ as the main barriers. ‘Cannot access treatment’ was reported by participants in all regions other than NCD. No reports of treatment denial or ‘local beliefs’, which pertain to local cultural fears such as a fear of sorcery were provided as reasons for not accessing cataract surgery services.

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Figure 3 Reported barriers to cataract surgery by sex

Figure 4 Reported barriers to cataract surgery by region

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

Need not felt Fear Cost Unaware treatment ispossible

Cannot accesstreatment

Male (n=181) Female (n=194)

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

Need not felt Fear Cost Unaware treatment ispossible

Cannot accesstreatment

NCD (n=33) Highlands (n=244) Coastal (n=80) Islands (n=18)

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Table 7 Cataract surgical outcomes in Papua New Guinea - by presenting visual acuity (PVA) and best-corrected visual acuity (BCVA)

Visual acuity Papua New Guinea, weighted average

PVA BCVA Eyes (%) Eyes (%)

Can see 6/12 93 (36.4) 112 (44.6) Cannot see 6/12 but can see 6/18 29 (13.6) 36 (16.7) Cannot see 6/18 but can see 6/60 44 (21.5) 27 (13.6) Cannot see 6/60 60 (28.2) 51 (25.1)

1.14 Refractive error and spectacle coverage The unadjusted prevalence of distance refractive error in PNG was estimated to be 8.2% (95%CI 6.7 – 9.7%) in adults aged 50 years and above. In each region, there was a higher prevalence of refractive error in males compared to females (Appendix 1,

Table 17). This however, was not statistically significant. Between regions, the prevalence of refractive error was significantly lower in the Highlands (4.3%, 95%CI 3.1 – 5.5%) compared to the other three regions (NCD: 10.2%, 95%CI 8.0-12.3%; Islands: 11.1%, 95%CI 9.1 – 13.2%; Coastal: 11.4%, 95%CI 7.6 – 15.3%).

Upon presentation, 3.4% of the study population had distance spectacles, although approximately 10% of these did not achieve VA of 6/12 or better. The lowest spectacle coverage was found in females in the Highlands (5.3%) and Islands (33.3%) regions. For males and females with distance refractive error, 65.7% and 71.2% were uncorrected, respectively (Appendix 1, Table 17)

For presbyopia, spectacle coverage was 17.5% of the sample population. Of those with near spectacles, a greater percentage of males (57.7%) presented with their spectacles compared to females (42.3%).

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Table 8 Prevalence of refractive error and uncorrected presbyopia of the sample population in Papua New Guinea

Prevalence of

Papua New Guinea, weighted average Total Male Female

n % n % n % Distance refractive error 416 8.2 225 8.8 191 7.6

Uncorrected distance refractive error

263 72.7 134 61.3 129 79.1

Uncorrected near refractive error 2,963 82.5 1,454 79.3 1,509 86.4

1.15 Diabetes and DR in National Capital District In our sample, 7.8% (95%CI 5.5 – 10.1%) of adults aged 50 years or older were defined as having diabetes. After adjusting for sex and age, the estimated prevalence of diabetes in the National Capital District was 8.1% (95%CI 5.7 – 10.4%) in adults aged 50 years or older. Of those with diabetes, 62.4% were newly-diagnosed (reported that they did not have diabetes, but RBG level was found to be ≥200mg/dL) and 37.6% reported that they had been previously diagnosed. Of the 35 participants with known diabetes, 71.4% had a RBG level of ≥200mg/dL; this suggested poor management of the disease. Table 9 presents the types of treatment reported by those with a previous diagnosis of diabetes. No participants reported management with insulin. Although participants with diabetes were surveyed on the type of treatment prescribed for diabetes management, no further questions were asked regarding how well management was adhered to. It is possible that those who reported not receiving treatment, might in fact not be adhering to treatment previously prescribed.

Table 9 Types of diabetes treatment reported in people with known diabetes

Treatment Male Female Total

n % n % n % Tablets 7 50.0 12 57.1 19 54.3 Diet only 3 21.4 4 19.0 7 20.0 None 4 28.6 5 23.8 9 25.7

Figure 5 shows the distribution of participants with known diabetes and the last eye examination for DR. Over 80% of participants with known diabetes reported never having had an eye examination for DR, while only 11.4% had an eye examination within the last 12 months. No participants reported having an eye examination 13 to 24 months prior.

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Figure 5 Proportion of participants with known diabetes and last eye examination for DR

Of all participants with diabetes (known and newly-diagnosed), almost half (46.4%) had some form of DR or maculopathy. Figure 6 provides a breakdown on the type and severity of DR.

Figure 6 Sample prevalence of DR in National Capital District * Diabetes indicates those who reported with known a diagnosis or having had a random blood glucose reading of ≥200mg/dL at the time of participation.

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

Males Females Total

Perc

enta

ge (%

)

Never had eye examination for DR 0-12 months ago >24 months ago

56.0

11.9

8.3

7.1

3.6

13.1

44.0

65.5

14.3

1.2

19.0

19.0

0 10 20 30 40 50 60 70 80

No retinopathy (R0)

Background DR - mild (R1)

Background DR - observable (R2)

Background DR - referable (R3)

Proliferative DR (R4)

Ungradable DR (R6)

Any retinopathy

No maculopathy (M0)

Maculopathy - observable (M1)

Maculopathy - referable (M2)

Ungradable Maculopathy (M6)

Any laser scars

% of people with diabetes*

31

Discussion

The estimated age- and sex-adjusted prevalence of blindness in people aged 50 years and older in PNG is 5.6% (95%CI 4.9 – 6.3%), and higher than the previous estimation of 3.9% (95%CI 3.4 – 6.1%).(5) Although, this suggests an increase in prevalence, this difference is not statistically significant. Direct comparisons between earlier estimates of prevalence of blindness and current estimates are to be taken with caution, as this study recruited a national representative sample, rather than participants from one urban and rural area near Port Moresby.

The prevalence of blindness in PNG is estimated to be higher than other Pacific Islands, which range between 0.5% to 3.6%.(12-14) With the exception of Fiji and Timor-Leste, the majority of these prevalence estimates in the Pacific were obtained at least five years ago. However the Fiji and Timor-Leste RAAB survey used different inclusion criteria (adults aged 40 years and over rather than adults 50 years and over) – as result these prevalence estimates are not directly comparable. Furthermore, whether the same definitions of blindness or whether a similar protocol to the RAAB survey was implemented for the remaining Pacific nations is unknown. In 2014, stakeholders from Samoa and the Solomon Islands have expressed interest in conducting a RAAB, however they are yet to conduct one.(16) RAAB surveys conducted in Cambodia, China, Philippines and Vietnam reported age- and sex-adjusted prevalence of blindness to be 3.4%, 2.7%, 2.5% and 1.8%, respectively.(16-19)

In line with findings from previous PNG, Cambodia, and Vietnam RAAB surveys, the main causes of blindness in this study were found to be untreated cataract (88.6%) and other posterior segment disease (3.9%).(5, 16, 19) The previous estimates of blindness and vision impairment in PNG reported that 73.2% of blindness was due to cataract compared with 81.8% in NCD and 91.0% in the Coastal region of this study. This may suggest an increase in the prevalence of cataract as the leading cause of blindness; however, this finding may also reflect the fact that more remote and rural locations were surveyed within these regions, where there is likely to be a higher frequency of untreated cataract.

The WHO recommend that CSC should be used as an indicator for the quality of care in the context of Universal Health Coverage, as it informs the degree to which services are meeting needs and can be used for monitoring purposes.(11) Based on available RAAB data in the repository, the global median CSC was 53.7% (IQR 46.1 - 66.6%) for operable cataracts where pinhole VA was < 6/60.(21) In comparison to developing countries in Southeast Asia, South Asia, Africa and South America, PNG had an estimated combined national CSC of 33.5%. Although CSC (VA<6/60) was lower than the estimated global median, a wide range was observed, with lowest coverage in females in the Highlands (9.2%) and highest in males in the Islands (78.3%). Previous CSC in PNG were reported to be 45.3%.(21) When compared to the current sample, CSC was approximately 40% in the corresponding regions. However, the comparison must be considered with caution considering the different sampling strategies used in the different studies.

32

Currently there are no recommended targets for CSC; nonetheless the WHO recommends that at least 80% of people receiving cataract surgery should have postoperative presenting VA of 6/18 or better, and that at most only 5% of patient should have postoperative presenting VA worse than 6/60.(23) From this survey, PNG is below the recommended target. However, available data from the RAAB repository shows that no country has yet achieved the recommended cataract surgery outcome targets.(21) In PNG, Fiji, and Samoa, ophthalmologists and trainees were reviewed on postoperative unaided visual acuity outcomes, which ranged from 41.5% to 74%.(23-25) Although outcomes were higher than this study, these were short-term (12 weeks) postoperative outcomes with variable response rates to follow ups and still below the WHO recommended target. The higher than recommended rate of poor cataract surgery outcome could be due to a number of factors including lack of follow up, as patients are unable to travel the often long distances required to access services, and facilities for the treatment of posterior capsular opacifications are overall limited. Ramke et al.(21) have recently introduced ‘effective CSC’ as an indicator that combines CSC and outcomes – this may be a useful approach for monitoring future progress in CSC in PNG.

‘Unaware [that cataract] treatment is possible’ and ‘Need [for surgery] not felt’ were the most commonly reported barriers to receiving cataract surgery in all regions of PNG, with the exception of the Coastal region. This suggests a need for improving eye health education among the older population on the availability and potential benefits of cataract surgery. For the Coastal region, this included provinces in the Momase and Papua regions (excluding Milne Bay Province). For eye clinics within these regions, participants in Papua region potentially need to travel to Port Moresby, where costs of cataract surgery are highest. The reported barrier of ‘cost’ to cataract surgery from participants in Coastal region might be a combination of travel and surgical costs. Having no participants reporting ‘local beliefs’ as a barrier to cataract surgery might be associated with the simple design. As this is only a rough survey on barriers, such reports on local beliefs might only be elicited with in-depth interviews where participants have the opportunity to elaborate on their challenges to accessing cataract surgical services.

The addition of early vision impairment to the survey highlighted the need for refractive services in all regions. Distance refractive error in adults over 50 years of age was estimated to be 8.2%, however of those with vision impairment due to distance refractive error, only 31.5% had appropriate correction. Near spectacle coverage was 17.5%, which is higher than India (11.1%), but lower than Timor-Leste (26.2%).(26, 27) This measurement of coverage however is assuming all adults 50 years and older need near correction. This calculation did not take into account participants with myopia that could achieve good near VA unaided therefore potentially underestimating coverage. Despite these assumptions though, the coverage is likely to be low. Spectacle coverage for distance and near was lower in females than males across all regions. Previous reports on female attitudes towards spectacle wear in PNG include fear of jealousy and feelings of shame might be attributable to low spectacle

33

coverage and females not accessing services. Overall, the outcomes indicate a need for accessible refractive error services across the whole country, in particular, the Highlands and for females.

The diabetes prevalence in adults aged 50 years and over was lower than previous reports in PNG (8.1% versus 14.4%), although previous assessments of diabetes have used different blood glucose assessment techniques, and age groups – making comparisons difficult. Previous reports of the prevalence of diabetes have ranged between 9.0% and 33%.(10, 28, 29) It is unclear whether the prevalence of diabetes found in this study is an under estimate, or if the prevalence of diabetes in PNG is significantly less than elsewhere in the Pacific region,(31) which has some of the highest rates globally. Regardless, as the rates of adults over 50 who were newly diagnosed (62.4%) was high, and almost half of those with diabetes had some form of DR or maculopathy, this indicates that undiagnosed diabetes and DR are likely to be increasingly significant public health issue in PNG with increasing rates of diabetes. It is important to note that results are for the NCD region only and can’t be generalised to the rest of the country, as there are likely to be diet and lifestyle factors that impact the prevalence of diabetes.(28, 29, 31)

Project Learnings

1.16 Training Overall the RAAB training with DR component conducted in November 2016 was a success. Although the training week was taxing, the survey team members were engaged and committed to the research project. Key indicators of the success of training include low inter-observer variability associated with RAAB procedures and DR grading. For RAAB processes of measuring visual acuity, lens examination and determining primary cause of reduced VA, all survey teams scored well above the threshold of 0.6 for most examinations, but all groups had up to two out of four examinations that scored below the threshold. These outcomes were attributed to the brief training duration, therefore suggesting future RAAB training could be extended to include additional practical work. For assessing the inter-observer variability in DR grading, it was identified the Certified DR Primary Grader was the only one able to obtain results over the 0.6 kappa coefficient threshold for both grading areas of maculopathy and retinopathy. This outcome might have been due to a grading system unfamiliar or not regularly used amongst the ophthalmologists. However, it suggests the importance of conducting inter-observer variability tests during training to identify whether one passing observer performs all DR screenings or additional training is required to standardise grading amongst ophthalmologists.

1.17 Logistics and study procedures Although the standardised RAAB manual training instructed survey teams to attend households one by one to identify eligible participants, it was identified that some of the study recruitment occurred in the community centre where people gathered, therefore, affecting

34

the compact segment sampling strategy. The congregation around a central area may be a common occurrence in Pacific Island communities where people prefer to gather when visitors attend to conduct research. The investigators were aware that having the approach of recruiting in the community centre could bias prevalence outcomes as those willing to attend and participate might be those seeking eye care due to a problem. Therefore, in order to minimise bias, each consenting participant was also asked whether there were other eligible participants within their home. If other eligible adults were present, they were included in the study and followed up with a visit to complete the eye examination. Once the cluster data collection was complete, additional basic eye examinations were delivered to other community members who wished to have an eye examination.

Other challenges faced during this study included uncontrollable environmental conditions such as poor weather, landslides, and rough seas resulting in delays of travelling to the selected clusters, as well as limited ability to communicate with the study teams in some areas due to a lack of telecommunications infrastructure. Additionally, local ethnic clashes resulted in some areas being too unstable for the study teams to visit (in these instances, the next nearest and safe available census unit was selected instead). Finally, the complexities involved with managing the logistics of multiple travelling teams and ensuring that they compensated in a timely manner cannot be underestimated – particularly in a country such as PNG, where there are often extended delays with electronic fund transfers. A key to the success of the survey was to initially train additional people so that the survey wasn’t delayed if a team member was unexpectedly unavailable.

1.18 Data collection tools – mobile phones versus paper Mobile phones and the mRAAB App were to be used to record data in all regions other than NCD. Use of smart phone technology has been mostly positive in this context, as it resulted in high data collection accuracy and low levels missing data due to the internal consistency checks require data collectors to submit all answers before progressing. Data managers outside PNG were able to respond to issues swiftly, increasing agility and decreasing time and cost as teams could quickly address where required.

Paper forms in NCD were required because the DR component was not available within mRAAB survey forms. Recording on paper survey forms required double data entry into the RAAB6 software in order to minimise data entry errors. Needing two entries per participant meant that more resources and time were required to complete data collection, processing and monitoring. In comparison to mRAAB data entry, delays in receiving paper data meant challenges were faced with providing NCD survey teams with immediate feedback or queries regarding data discrepancies.

The widespread nature of the Coastal Region meant some sample clusters were geographically closer to Port Moresby. Logistically, these were more easily accessed by an NCD survey team. As the NCD team were comfortable with recording data on paper survey forms, it became apparent that they continued to do so in the Coastal region clusters rather

35

than recording in mRAAB. This unfortunately led to additional time and resources in completing double data entry for these clusters and thus highlighting the advantages of using mobile phones for data collection.

With each survey, learnings from the use of mobile phones for data collection have been assessed. Additional time spent on training has mitigated ‘fear’ of technology. Cultural understanding of the ‘communal’ use of phones and data has also been taken into account in budgeting. Overall, the experience has been positive through the reduction of time and cost, which therefore is highly recommended for future large population-based studies.

1.19 Other strengths and limitations This is the first population-based assessment of blindness and vision impairment across all provinces of PNG and assessment of DR in the NCD region. Overall there was a high response rate, as less than 4% refused to participate and despite geographic, logistic and safety issues, there was low missing data and high coverage.

Achieving a national prevalence of blindness of 5.6% was greater the anticipated prevalence of 3.9% ± 0.8% (20% relative precision) suggesting sample size and power were adequate for estimating blindness. Furthermore, taking into account the sample participants age and sex were relatively similar to the census population data, it may be concluded the sample was a good representative of the population. However, as the sample size for each region was not sufficiently powered to estimate the prevalence of blindness at the regional level, caution must be exercised when reviewing these regional blindness estimates.

Due to the standard RAAB protocol for assessing vision, the true prevalence of distance refractive error may have been overestimated without objective or subjective refraction. Those presenting with distance correction were assessed with spectacles, however some spectacles might have had no significant prescription but rather only photochromatic lenses that are worn to alleviate glare symptoms and do not need to be removed indoors.

Similarly for the RAAB+DR standard protocol, newly diagnosed diabetes was dependent on a single RBG level ≥200 mg/dL. While current recommendations for the diagnosis of diabetes can be either a RBG ≥200 mg/dL, which should be accompanied with classic symptoms of hyperglycaemia or hyperglycaemic crisis, or two fasting (>8 hours) blood glucose level measurements ≥126 mg/dL.(33) As diabetes symptoms and fasting questions were not part of the survey, the estimation on the prevalence of diabetes may be under- or over-estimated.

36

Conclusion

Overall, this is the first population-based assessment of blindness and vision impairment across all provinces of PNG and diabetic retinopathy screening in NCD. The high prevalence of blindness that is largely due to cataracts suggests the need to address the accessibility of cataract surgical services across the country and advocacy for educating elderly patients on avoidable blindness. Furthermore, the low coverage of corrected refractive error indicates the necessity of further developing refractive services. There is a particular need for services for females across the country, and people in the Highlands. Although diabetes rates were lower than expected, the high numbers of participants that were unaware they had diabetes, the high levels of poor diabetes control and high rates of DR, suggest that there is a significant need for primary diabetes and eye care services to provide regular eye examinations among people with diabetes.

Achieving equitable access to eye care services for both males and females and those from remote areas will be a long-term goal in PNG. Ongoing advocacy to increase services and improve services and support, particularly for women and those from rural areas, to engage with eye care services is required to reduce the inequities in eye health that exist in PNG. Developing and evaluating a comprehensive model of eye care, which includes eye care services for people with diabetes will be important next steps for improving the eye health of people in PNG.

37

References

1. Bourne RRA, Flaxman SR, Braithwaite T, Cicinelli MV, Das A, Jonas JB, et al. Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis. Lancet Glob Health. 2017.

2. National Statistical Office of Papua New Guinea. 2011 National Population and Housing Census of Papua New Guinea. Port Moresby, Papua New Guinea; 2011.

3. World Health Organization. Papua New Guinea Country Profile 2011. World Health Oganization Western Pacific Region; 2011.

4. National Statistical Office of Papua New Guinea. Papua New Guinea Demographic and Health Survey 2006. Port Moresby, Papua New Guinea; 2009.

5. Garap JN, Sheeladevi S, Shamanna BR, Nirmalan PK, Brian G, Williams C. Blindness and vision impairment in the elderly of Papua New Guinea. Clin Exp Ophthalmol. 2006;34(4):335-41.

6. Burnett A, Yu M, Paudel P, Naduvilath T, Fricke TR, Hani Y, et al. Perceptions of Eye Health and Eye Health Services among Adults Attending Outreach Eye Care Clinics in Papua New Guinea. Ophthalmic Epidemiol. 2015;22(6):361-9.

7. World Health Organization. Papua New Guinea 2016 [Available from: http://www.who.int/diabetes/country-profiles/png_en.pdf?ua=1.

8. Ogle GD. Type 2 diabetes mellitus in Papua New Guinea--an historical perspective. P N G Med J. 2001;44(3-4):81-7.

9. Taufa T, Benjamin AL. Diabetes: the by-product of westernization in Papua New Guinea. P N G Med J. 2001;44(3-4):108-10.

10. National Department of Health Papua New Guinea, HOPE Worldwide Papua New Guinea, Organization WH. Papua New Guinea NCD Risk Factors STEPS Report. Port Moresby, Papua New Guinea; 2014.

11. World Health Organization. Universal eye health: a global action plan 2014-2019. Spain2013.

12. Limburg H, Meester W, Kuper H, Polack S. Rapid Assessment of Avoidable Blindness (RAAB6). London, UK: International Centre for Eye Health London School of Hygiene and Tropical Medicine; 2013.

13. International Agency for the Prevention of Blindness. Western Pacific Regional Update and Country Profiles. Melbourne, Victoria; 2013.

14. Ramke J, Brian G, Maher L, Qalo Qoqonokana M, Szetu J. Prevalence and causes of blindness and low vision among adults in Fiji. Clin Exp Ophthalmol. 2012;40(5):490-6.

15. Ramke J, Brian G, Naduvilath T, Lee L, Qoqonokana MQ. Prevalence and Causes of Blindness and Low Vision Revisited after 5 years of Eye Care in Timor-Leste. Ophthalmic Epidemiol. 2012;19(2):52-7.

16. International Agency for the Prevention of Blindness Council of Members. Reporting regional progress in Western Pacific against the three objectives of ‘Universal Eye Health: A Global Action Plan 2014-2019’. United Kingdom: International Agency for the Prevention of Blindness; 2014.

17. Morchen M, Langdon T, Ormsby GM, Meng N, Seiha D, Piseth K, et al. Prevalence of blindness and cataract surgical outcomes in Takeo Province, Cambodia. Asia Pac J Ophthalmol (Phila). 2015;4(1):25-31.

18. Wu M, Yip JL, Kuper H. Rapid assessment of avoidable blindness in Kunming, china. Ophthalmology. 2008;115(6):969-74.

38

19. Eusebio C, Kuper H, Polack S, Enconado J, Tongson N, Dionio D, et al. Rapid assessment of avoidable blindness in negros island and antique district, Philippines. British Journal of Ophthalmology. 2007;91(12):1588-92.

20. Medical Service Administration of Viet Nam Ministry of Health, Viet Nam National Institute of Ophthalmology. National Survey on Avoidable Blindness Viet Nam. Hanoi, Vietnam; 2015.

21. Ramke J, Gilbert CE, Lee AC, Ackland P, Limburg H, Foster A. Effective cataract surgical coverage: An indicator for measuring quality-of-care in the context of Universal Health Coverage. PLoS One. 2017;12(3):e0172342.

22. Garap JN, Sheeladevi S, Brian G, Shamanna B, Nirmalan PK, Williams C. Cataract and its surgery in Papua New Guinea. Clin Exp Ophthalmol. 2006;34(9):880-5.

23. World Health Organization. Informal Consultation on Analysis of Blindness Prevention Outcomes WHO/PBL/98.68 Geneva, Switzerland: Programme for the Prevention of Blindness and Deafness; 1998 [Available from: http://apps.who.int/iris/bitstream/10665/67843/1/WHO_PBL_98.68.pdf.

24. Pathak HD. Annual Cataract Surgical Outcomes in (Western) Samoa, a Pacific Island Nation: A Very First Analysis. Samoa: University of Seychelles; 2009.

25. Bhikoo R, Vellara H, Lolokabaira S, Murray N, Sikivou B, McGhee C. Short-term outcomes of small incision cataract surgery provided by a regional population in the Pacific. Clin Exp Ophthalmol. 2017.

26. Pahau D, Melengas S, Garap J, Brian G. Monitoring cataract surgery outcomes in Papua New Guinea. Clin Exp Ophthalmol. 2006;34(9):900-2.

27. Marmamula S, Madala SR, Rao GN. Prevalence of uncorrected refractive errors, presbyopia and spectacle coverage in marine fishing communities in South India: Rapid Assessment of Visual Impairment (RAVI) project. Ophthalmic Physiol Opt. 2012;32(2):149-55.

28. Ramke J, du Toit R, Palagyi A, Brian G, Naduvilath T. Correction of refractive error and presbyopia in Timor-Leste. Br J Ophthalmol. 2007;91(7):860-6.

29. Benjamin AL. Community screening for diabetes in the National Capital District, Papua New Guinea: is betelnut chewing a risk factor for diabetes? P N G Med J. 2001;44(3-4):101-7.

30. Dowse GK, Spark RA, Mavo B, Hodge AM, Erasmus RT, Gwalimu M, et al. Extraordinary prevalence of non-insulin-dependent diabetes mellitus and bimodal plasma glucose distribution in the Wanigela people of Papua New Guinea. Med J Aust. 1994;160(12):767-74.

31. Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract. 2011;94(3):311-21.

32. Rarau P, Vengiau G, Gouda H, Phuanukoonon S, Kevau IH, Bullen C, et al. Prevalence of non-communicable disease risk factors in three sites across Papua New Guinea: a cross-sectional study. BMJ Global Health. 2017;2(2):e000221.

33. American Diabetes Association. 2. Classification and Diagnosis of Diabetes. Diabetes Care. 2017;40(Supplement 1):S11-S24.

39

Appe

ndix

1 –

Add

ition

al re

sults

Tabl

e 10

Age

and

sex

dist

ribut

ion

of su

rvey

regi

on a

nd sa

mpl

e po

pula

tion

in P

apua

New

Gui

nea(

2)

Regi

on

Age

grou

p (y

ears

) M

ale

n (%

) Fe

mal

e n

(%)

Tota

l n (%

) RA

AB S

ampl

e Su

rvey

regi

on

RAAB

Sam

ple

Surv

ey re

gion

RA

AB S

ampl

e Su

rvey

regi

on

NCD

50 -

59

345

(64.

5%)

11,6

84 (6

6%)

496

(75.

5%)

8,34

2 (6

6.9%

) 84

1 (7

0.6%

) 20

,026

(66.

4%)

60 -

69

134

(25%

) 4,

455

(25.

2%)

134

(20.

4%)

2,98

4 (2

3.9%

) 26

8 (2

2.5%

) 7,

439

(24.

7%)

70 -

79

46 (8

.6%

) 1,

228

(6.9

%)

22 (3

.3%

) 84

5 (6

.8%

) 68

(5.7

%)

2,07

3 (6

.9%

) 80

- 99

10

(1.9

%)

324

(1.8

%)

5 (0

.8%

) 29

8 (2

.4%

) 15

(1.3

%)

622

(2.1

%)

Tota

l 53

5 (1

00%

) 17

,691

(100

%)

657

(100

%)

12,4

69 (1

00%

) 1,

192

(100

%)

30,1

60 (1

00%

)

High

land

s

50 -

59

364

(50.

8%)

99,0

89 (5

4.6%

) 31

1 (6

3.7%

) 82

,342

(58.

8%)

675

(56%

) 18

1,43

1 (5

6.4%

) 60

- 69

22

4 (3

1.2%

) 58

,330

(32.

2%)

141

(28.

9%)

43,1

47 (3

0.8%

) 36

5 (3

0.3%

) 10

1,47

7 (3

1.6%

) 70

- 79

10

1 (1

4.1%

) 19

,350

(10.

7%)

22 (4

.5%

) 11

,711

(8.4

%)

123

(10.

2%)

31,0

61 (9

.7%

) 80

- 99

28

(3.9

%)

4,65

9 (2

.6%

) 14

(2.9

%)

2,86

3 (2

%)

42 (3

.5%

) 7,

522

(2.3

%)

Tota

l 71

7 (1

00%

) 18

1,42

8 (1

00%

) 48

8 (1

00%

) 14

0,06

3 (1

00%

) 12

05 (1

00%

) 32

1,49

1 (1

00%

)

Coas

tal

50 -

59

308

(49.

1%)

72,2

89 (5

5.4%

) 28

7 (4

6.7%

) 66

,015

(55.

9%)

595

(47.

9%)

138,

304

(55.

6%)

60 -

69

180

(28.

7%)

38,5

51 (2

9.6%

) 18

8 (3

0.6%

) 34

,951

(29.

6%)

368

(29.

6%)

73,5

02 (2

9.6%

) 70

- 79

10

4 (1

6.6%

) 15

,379

(11.

8%)

96 (1

5.6%

) 13

,448

(11.

4%)

200

(16.

1%)

28,8

27 (1

1.6%

) 80

- 99

35

(5.6

%)

4,18

8 (3

.2%

) 44

(7.2

%)

3,73

7 (3

.2%

) 79

(6.4

%)

7,92

5 (3

.2%

) To

tal

627

(100

%)

130,

407

(100

%)

615

(100

%)

118,

151

(100

%)

1242

(100

%)

248,

558

(100

%)

Isla

nds

50 -

59

293

(48.

9%)

39,5

11 (5

7%)

321

(55.

3%)

34,7

76 (5

7.2%

) 61

4 (5

2.1%

) 74

,287

(57.

1%)

60 -

69

181

(30.

2%)

19,3

29 (2

7.9%

) 14

8 (2

5.5%

) 16

,906

(27.

8%)

329

(27.

9%)

36,2

35 (2

7.8%

) 70

- 79

86

(14.

4%)

7,90

8 (1

1.4%

) 72

(12.

4%)

6,93

8 (1

1.4%

) 15

8 (1

3.4%

) 14

,846

(11.

4%)

80 -

99

39 (6

.5%

) 2,

549

(3.7

%)

39 (6

.7%

) 2,

204

(3.6

%)

78 (6

.6%

) 4,

753

(3.7

%)

Tota

l 59

9 (1

00%

) 69

,297

(100

%)

580

(100

%)

580

(100

%)

1,17

9 (1

00%

) 13

0,12

1 (1

00%

)

40

Tabl

e 11

Sam

ple

prev

alen

ce o

f blin

dnes

s and

visi

on im

pairm

ent i

n th

e fo

ur re

gion

s of P

apua

New

Gui

nea

- By

eyes

and

indi

vidu

als w

ith a

vaila

ble

corr

ectio

n

N

atio

nal C

apita

l Dis

tric

t H

ighl

ands

Co

asta

l Is

land

s M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5% C

I)

Blin

dnes

sa

Indi

vidu

als*

19

3.

6 (2

.2-4

.9)

14

2.1

(1.1

-3.2

) 55

7.

7 (5

.2-1

0.2)

49

10

.0 (7

.1-1

3.0)

26

4.

2 (2

.7-5

.6)

41

6.7

(4.6

-8.7

) 6

1.0

(0.0

-2.0

) 15

2.

6 (1

.4-3

.8)

Eyes

84

7.

9 (6

.2-9

.5)

70

5.3

(3.5

-7.1

) 18

7 13

.0 (1

0.1-

16.0

) 15

1 15

.5 (1

1.8-

19.1

) 14

0 11

.2 (

9.1-

13.2

) 14

7 12

.0 (9

.7-1

4.2)

58

4.

8 (3

.2-6

.5)

69

6.0

(4.2

-7.7

)

Seve

re v

isio

n im

pairm

entb

Indi

vidu

als

13

2.4

(1.2

-3.7

) 5

0.8

(0.2

-1.4

) 30

4.

2 (2

.3-6

.1)

16

3.3

(1.6

-5.0

) 20

3.

2 (1

.7-4

.6)

23

3.7

(1.6

-5.8

) 7

1.2

(0.4

-1.9

) 8

1.4

(0.5

-2.3

)

Eyes

41

3.

8 (2

.7-5

.0)

25

1.9

(1.1

-2.7

) 88

6.

1 (4

.4-7

.9)

33

3.4

(2.2

-4.5

) 52

4.

2 (2

.9-5

.4)

64

5.2

(3.2

-7.2

) 28

2.

3 (1

.4-3

.3)

19

1.6

(0.7

-2.5

)

Mod

erat

e vi

sion

impa

irmen

tc

Indi

vidu

als

34

6.4

(4.9

-7.8

) 39

5.

9 (3

.7-8

.1)

83

11.6

(9.6

-13.

6)

48

9.8

(6.7

-13.

0)

90

14.4

(10.

8-17

.9)

111

18.1

(13.

6-22

.5)

41

6.8

(4.5

-9.2

) 46

7.

9 (5

.3-1

0.6)

Eyes

76

7.

1 (5

.4-8

.8)

84

6.4

(4.6

-8.2

) 17

7 2.

3 (1

0.3-

14.4

) 93

9.

5 (7

.1-1

2.0)

17

8 14

.2 (1

1.4-

17.0

) 23

7 19

.3 (1

5.3-

23.2

) 10

6 8.

9 (6

.5-1

1.2)

11

4 9.

8 (7

.3-1

2.4)

Early

vis

ion

impa

irmen

td

Indi

vidu

als

46

8.6

(5.8

-11.

4)

38

5.8

(3.8

-7.8

) 61

8.

5 (6

.8-1

0.2)

28

5.

7 (4

.0-7

.5)

56

8.9

(6.1

-11.

8)

51

8.3

(5.4

-11.

2)

46

7.7

(5.3

-10.

1)

39

6.7

(4.4

-9.0

)

Eyes

10

4 9.

7 (6

.9-1

2.5)

96

7.

3 (5

.5-9

.1)

129

9.0

(7.4

-10.

6)

67

6.9

(5.0

-8.7

) 12

9 10

.3 (7

.7-1

2.8)

10

2 8.

3 (5

.8-1

0.8)

10

1 8.

4 (6

.6-1

0.3)

95

8.

2 (6

.3-1

0.1)

*Dat

a fo

r ind

ivid

uals

refe

rs to

bila

tera

l cas

es; 9

5% C

I = 9

5% c

onfid

ence

inte

rval

a Blin

dnes

s: V

A <3

/60;

b Se

vere

visi

on im

pairm

ent:

VA <

6/60

but

≥3/

60; c

Mod

erat

e vi

sion

impa

irmen

t: VA

<6/

18 b

ut ≥

6/60

, d Ea

rly v

ision

impa

irmen

t VA

<6/1

2 bu

t ≥6/

18

41

Tabl

e 12

Prin

cipa

l cau

ses o

f blin

dnes

s and

visi

on im

pairm

ent o

f ind

ivid

uals

in th

e fo

ur re

gion

s of P

apua

New

Gui

nea

N

atio

nal C

apita

l Dis

tric

t Hi

ghla

nds

Coas

tal

Isla

nds

Fr

eque

ncy

(%)

Freq

uenc

y (%

) Fr

eque

ncy

(%)

Freq

uenc

y (%

)

Caus

e B

(n=3

3)

SVI

(n=1

8)

MVI

(n

=73)

EV

I (n

=84)

B

(n=1

04)

SVI

(n=4

6)

MVI

(n

=131

) EV

I (n

=89)

B

(n=6

7)

SVI

(n=4

3)

MVI

(n

=201

) EV

I (n

=107

) B

(n=2

1)

SVI

(n=1

5)

MVI

(n

=87)

EV

I (n

=85)

Refr

activ

e er

ror

0 (0

.0)

1 (5

.6)

19 (2

6.0)

49

(58.

3)

0 (0

.0)

0 (0

.0)

3 (2

.3)

12 (1

3.5)

0

(0.0

) 0

(0.0

) 37

(18.

4)

44 (4

1.1)

0

(0.0

) 1

(6.7

) 24

(27.

6)

60 (7

0.6)

Cata

ract

, un

trea

ted

27

(81.

8)

14

(77.

8)

43 (5

8.9)

23

(27.

4)

94

(90.

4)

44 (9

5.7)

11

7 (8

9.3)

66

(74.

2)

61

(91.

0)

39 (9

0.7)

15

4 (7

6.6)

56

(52.

3)

17 (8

1.0)

11

(73.

3)

54 (6

2.1)

9

(10.

6)

Cata

ract

surg

ical

co

mpl

icat

ions

1

(3.0

) 0

(0.0

) 1

(1.4

) 0

(0.0

) 1

(1.0

) 0

(0.0

) 2

(1.5

) 4

(4.5

) 1

(1.5

) 0

(0.0

) 3

(1.5

) 0

(0.0

) 0

(0.0

) 1

(6.7

) 1

(1.1

) 1

(1.2

)

Trac

hom

atou

s co

rnea

l opa

city

0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 1

(4.8

) 0

(0.0

) 0

(0.0

) 0

(0.0

)

Non

-tr

acho

mat

ous

corn

eal o

paci

ty

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

2 (1

.9)

1 (2

.2)

0 (0

.0)

0 (0

.0)

0 (0

.0)

1 (2

.3)

0 (0

.0)

0 (0

.0)

1 (4

.8)

0 (0

.0)

0 (0

.0)

0 (0

.0)

Phth

isis

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

1 (2

.2)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

DR

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

0 (0

.0)

1 (6

.7)

0 (0

.0)

1 (1

.2)

Age-

rela

ted

mac

ular

de

gene

ratio

n 1

(3.0

) 0

(0.0

) 0

(0.0

) 1

(1.2

) 1

(1.0

) 0

(0.0

) 2

(1.5

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 2

(1.0

) 1

(0.9

) 0

(0.0

) 1

(6.7

) 3

(3.4

) 8

(9.4

)

Oth

er p

oste

rior

segm

ent d

iseas

e 3

(9.1

) 3

(16.

7)

10 (1

3.7)

11

(13.

1)

4 (3

.8)

0 (0

.0)

7 (5

.3)

7 (7

.9)

2 (3

.0)

1 (2

.3)

5 (2

.5)

6 (5

.6)

1 (4

.8)

0 (0

.0)

5 (5

.7)

7 (8

.2)

All o

ther

gl

obe/

CNS

abno

rmal

ities

1

(3.0

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 2

(1.9

) 0

(0.0

) 0

(0.0

) 0

(0.0

) 3

(4.5

) 2

(4.7

) 0

(0.0

) 0

(0.0

) 1

(4.8

) 0

(0.0

) 0

(0.0

) 0

(0.0

)

NO

TE: N

o oc

curr

ence

s of p

rese

ntin

g vi

sual

acu

ity o

f <6/

12 w

ere

the

prim

ary

caus

e du

e to

unc

orre

cted

aph

akia

, Eal

es’ d

iseas

e or

gla

ucom

a

42

Tabl

e 13

Age

- and

sex-

adju

sted

pre

vale

nce

of b

lindn

ess a

nd v

ision

impa

irmen

t in

indi

vidu

als a

nd e

yes w

ith a

vaila

ble

corr

ectio

n in

the

four

regi

ons

of P

apua

New

Gui

nea

Nat

iona

l Cap

ital D

istr

ict

Hig

hlan

ds

Coas

tal

Isla

nds

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI

) n

% (9

5%

CI)

Blin

dnes

sa

Indi

vidu

als*

60

7 3.

4 (2

.1 -

4.7)

37

5 3.

0 (2

.0 -

4.0)

11

,963

6.

6

(4.1

- 9.

1)

15,4

80

11.1

(8

.1 -

14.0

) 4,

438

3.4

(2

.0 -

4.8)

6,

044

5.1

(3

.1 -

7.2)

48

7 0.

7

(0.0

- 1.

7)

1,35

2 2.

2

(1.0

- 3.

4)

Eyes

2,

740

7.7

(6.1

- 9.

4)

1,69

4 6.

8 (5

.0 -

8.6)

42

,632

11

.7

(8.8

- 14

.7)

46,8

05

16.7

(1

3.1

- 20

.3)

25,9

09

9.9

(7.9

- 12

.0)

22,6

88

9.6

(7.4

- 11

.8)

5,45

9 3.

9 (2

.3 -

5.6)

6,

758

5.6

(3.8

- 7.

3)

Seve

re v

isio

n im

pairm

entb

Indi

vidu

als

407

2.3

(1.0

- 3.

6)

89

0.7

(0.1

- 1.

3)

6,91

2 3.

8

(1.9

- 5.

7)

5,22

5 3.

7

(2.1

- 5.

4)

3,81

8 2.

9

(1.5

- 4.

4)

3,57

8 3.

0

(0.9

- 5.

1)

721

1.0

(0

.3 -

1.8)

76

9 1.

3

(0.3

- 2.

2)

Eyes

1,

288

3,6

(2.5

- 4.

8)

545

2.2

(1.4

- 3.

0)

20,8

92

5.8

(4.0

- 7.

5)

10,7

56

3.8

(2.7

- 5.

0)

9,85

7 3.

8 (2

.5 -

5.0)

10

,503

4.

4 (2

.4 -

6.5)

2,

863

2.1

(1.2

- 3.

0)

1,69

5 1.

4 (0

.5 -

2.3)

M

oder

ate

visi

on im

pairm

entc

Indi

vidu

als

1,08

1 6.

1

(4.7

- 7.

5)

1,01

9 8.

2

(6.0

- 10

.4)

19,4

51

10.7

(8

.7 -

12.7

) 15

,018

10

.7

(7.6

- 13

.8)

16,2

32

12.4

(8

.9 -

16.0

) 18

,573

15

.7

(11.

3 - 2

0.2)

3,

906

5.6

(3

.2 -

8.0)

4,

183

6.9

(4

.3 -

9.5)

Eyes

2,

426

6.9

(5.2

- 8.

5)

2,05

2 8.

2 (6

.4 -

10.0

) 42

,158

11

.6

(9.6

- 13

.6)

28,8

09

10.3

(7

.8 -

12.7

) 33

,181

12

.7

(9.9

- 15

.5)

41,6

40

17.6

(1

3.7

- 21.

5)

10,4

85

7.6

(5.2

- 9.

9)

10,5

26

8.7

(6.1

- 11

.2)

Early

visi

on im

pairm

entd

Indi

vidu

als

1,48

8 8.

4 (5

.6 -

11.3

) 87

7 7.

0 (5

.1 -

9.0)

14

,615

8.

1 (6

.4 -

9.7)

8,

137

5.8

(4

.1 -

7.6)

10

,798

8.

3

(5.5

- 11

.1)

8,92

1 7.

6

(4.7

- 10

.4)

4,55

4 6.

6

(4.2

- 8.

9)

3,74

4 6.

2

(3.9

- 8.

5)

Eyes

3,

360

9.5

(6.7

- 12

.3)

2,03

6 8.

2 (6

.4 -

9.9)

31

,615

8.

7 (7

.1 -

10.3

) 19

,906

7.

1 (5

.2 -

9.0)

25

,517

9.

8 (7

.2 -

12.3

) 18

,132

7.

7 (5

.2 -

10.2

) 10

,369

7.

5 (5

.6 -

9.3)

9,

490

7.8

(5.9

- 9.

7)

NO

TE: D

ata

for i

ndiv

idua

ls re

fers

to b

ilate

ral c

ases

a Bl

indn

ess i

ndic

ates

VA

<3/6

0; b

Seve

re v

ision

impa

irmen

t (SV

I) in

dica

tes V

A <6

/60

but ≥

3/60

; c M

oder

ate

visio

n im

pairm

ent (

MVI

) ind

icat

es V

A <6

/18

but ≥

6/60

; d Ea

rly v

ision

impa

irmen

t (EV

I) in

dica

tes V

A <6

/12

but ≥

6/18

43

Tabl

e 14

Age

- and

sex-

adju

sted

pre

vale

nce

of c

atar

act (

bila

tera

l ind

ivid

uals

and

tota

l cat

arac

t eye

s) in

four

regi

ons o

f Pap

ua N

ew G

uine

a - w

ith

best

-cor

rect

ed o

r pin

hole

visu

al a

cuity

Visu

al a

cuity

Nat

iona

l Cap

ital D

istr

ict

Hig

hlan

ds

Coas

tal

Isla

nds

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI)

n %

(95%

CI

) n

% (9

5% C

I) n

% (9

5% C

I) n

% (9

5%

CI)

< 3/

60

Indi

vidu

als

253

1.4

(0.6

- 2.

3)

215

1.7

(1.0

- 2.

4)

8,79

0 4.

8 (2

.8 -

6.9)

14

,417

10

.3

(7.5

- 13

.1)

3,03

8 2.

3 (0

.8 -

3.9)

4,

491

3.8

(2.0

- 5.

6)

330

0.5

(0.0

- 1.

1)

421

0.7

(0.0

- 1.

3)

Eyes

1,

225

3.5

(2

.4 -

4.5)

96

9 3.

9

(2.9

- 4.

9)

31,1

42

8.6

(6

.0 -

11.1

) 40

,915

14

.6

(11.

2 -1

8.0)

14

,875

5.

7

(3.8

- 7.

6)

15,9

91

6.8

(4

.8 -

8.7)

2,

603

1.9

(0

.9 -

2.8)

3,

047

2.5

(1

.4 -

3.6)

<

6/60

- 3/

60

Indi

vidu

als

155

0.9

(0.0

- 1.

8)

72

0.6

(0.0

- 1.

1)

5,03

8 2.

8 (1

.3 -

4.2)

4,

349

3.1

(1.6

- 4.

6)

977

0.7

(0.0

- 1.

5)

1,13

0 1.

0 (0

.0 -

2.6)

65

0.

1 (0

.0 -

0.4)

31

7 0.

5 (0

.0 -

1.1)

Eyes

28

2 0.

8

(0.0

- 1.

7)

333

1.3

(0

.7 -

1.9)

16

,955

4.

7

(3.3

- 6.

0)

9,57

3 3.

4

(2.2

- 4.

6)

2,63

6 1.

0

(0.2

- 1.

8)

3,29

4 1.

4 (0

.0 -

2.9)

71

5 0.

5

(0.0

- 1.

0)

1,09

2 0.

9

(0.3

- 1.

5)

< 6/

18 -

6/60

Indi

vidu

als

413

2.3

(1.2

- 3.

5)

394

3.2

(1

.6 -

4.7)

11

,018

6.

1 (3

.5 -

8.7)

8,

816

6.3

(4.1

- 8.

5)

9,20

4 7.

1 (4

.9 -

9.2)

9,

097

7.7

(4.3

- 11

.1)

984

1.4

(0.4

- 2.

4)

773

1.3

(0.3

- 2.

2)

Eyes

1,

204

3.4

(2

.1 -

4.7)

70

8 2.

8

(1.6

- 4.

1)

25,9

69

7.2

(4

.9 -

9.4)

16

,166

5.

8 (4

.0 -

7.6)

22

,669

8.

7

(6.1

- 11

.3)

23,6

31

10.0

(6

.7 -

13.3

) 3,

190

2.3

(1

.2 -

3.4)

2,

553

2.1

(1.0

- 3.

2)

< 6/

12 -

6/18

Indi

vidu

als

718

4.1

(2.5

- 5.

6)

569

4.6

(3.1

- 6.

0)

12,3

68

6.8

(5.2

- 8.

4)

7,44

8 5.

3 (3

.6 -

7.1)

8,

520

6.5

(3.9

- 9.

2)

10,7

94

9.1

(7.0

- 11

.2)

2,22

3 3.

2 (1

.5 -

4.9)

2,

204

3.6

(1.7

- 5.

5)

Eyes

1,

550

4.4

(3

.0 -

5.8)

1,

267

5.1

(3

.5 -

6.7)

28

,064

7.

7

(6.3

- 9.

2)

17,1

96

6.1

(4

.5 -

7.8)

19

,167

7.

3

(5.0

- 9.

7)

21,1

84

9.0

(6.0

- 12

.0)

6,26

1 4.

5 (2

.7 -

6.4)

5,

279

4.3

(2.5

- 6.

1)

44

Tabl

e 15

Cat

arac

t sur

gica

l cov

erag

e (u

nadj

uste

d) a

s a p

erce

ntag

e of

indi

vidu

als a

nd e

yes i

n th

e fo

ur re

gion

s of P

apua

New

Gui

nea

Visu

al a

cuity

N

atio

nal C

apita

l Dis

tric

t H

ighl

ands

Co

asta

l Is

land

s M

ale

(%)

Fem

ale

(%)

p M

ale

(%)

Fem

ale

(%)

p M

ale

(%)

Fem

ale

(%)

p M

ale

(%)

Fem

ale

(%)

p <

3/60

In

divi

dual

s 50

.0

42.9

0.

81

30.5

11

.5

0.02

42

.4

34.0

0.

45

81.0

60

.0

0.62

Ey

es

38.7

21

.6

0.05

21

.5

7.8

<0.0

01

33.3

23

.7

0.08

64

.0

38.8

0.

01

< 6/

60

Indi

vidu

als

38.1

33

.3

0.82

25

.0

9.2

0.04

38

.5

28.6

0.

48

78.3

46

.7

0.35

Ey

es

33.8

16

.9

0.02

15

.3

6.5

0.01

29

.8

20.2

0.

05

57.8

30

.6

0.00

1 <

6/18

In

divi

dual

s 27

.8

18.2

0.

45

18.5

6.

5 0.

02

23.5

14

.8

0.18

59

.5

37.0

0.

30

Eyes

22

.0

12.0

0.

06

10.6

5.

0 0.

02

15.9

10

.8

0.07

41

.0

20.9

0.

002

45

Tabl

e 16

Cat

arac

t sur

gica

l out

com

es in

the

four

regi

ons o

f Pap

ua N

ew G

uine

a –

by p

rese

ntin

g (P

VA) a

nd b

est-

corr

ecte

d vi

sual

acu

ity (B

CVA)

Visu

al a

cuity

Nat

iona

l Cap

ital D

istr

ict (

n=35

) H

ighl

ands

(n=4

9)

Coas

tal (

n=75

) Is

land

s (n=

67)

PVA

BCVA

PV

A BC

VA

PVA

BCVA

PV

A BC

VA

Eyes

(%)

Eyes

(%)

Eyes

(%)

Eyes

(%)

Eyes

(%)

Eyes

(%)

Eyes

(%)

Eyes

(%)

Can

see

6/12

13

(37.

1)

17 (4

8.6)

12

(24.

5)

15 (3

0.6)

33

(44.

0)

42 (5

6.0)

35

(52.

2)

38 (5

6.7)

Cann

ot se

e 6/

12 b

ut c

an se

e 6/

18

4 (1

1.4)

5

(14.

3)

7 (1

4.3)

10

(20.

4)

11 (1

4.7)

8

(10.

7)

7 (1

0.4)

13

(19.

4)

Cann

ot se

e 6/

18 b

ut c

an se

e 6/

60

5 (1

4.3)

3

(8.6

) 12

(24.

5)

7 (1

4.3)

16

(21.

3)

13 (1

7.3)

11

(16.

4)

4 (6

.0)

Cann

ot se

e 6/

60

13 (3

7.1)

10

(28.

6)

18 (3

6.7)

17

(34.

7)

15 (2

0.0)

12

(16.

0)

14 (2

0.9)

12

(17.

9)

Tabl

e 17

Pre

vale

nce

of re

frac

tive

erro

r of t

he sa

mpl

e po

pula

tion

in th

e fo

ur re

gion

s of P

apua

New

Gui

nea

Refr

activ

e er

ror t

ype

Nat

iona

l Cap

ital D

istr

ict

Hig

hlan

ds

Coas

tal

Isla

nds

Mal

e Fe

mal

e M

ale

Fem

ale

Mal

e Fe

mal

e M

ale

Fem

ale

n %

(9

5%CI

) n

%

(95%

CI)

n %

(9

5%CI

) n

%

(95%

CI)

n %

(9

5%CI

) n

%

(95%

CI)

n %

(9

5%CI

) n

%

(95%

CI)

Dist

ance

refr

activ

e er

ror

68

12.7

(9

.5 -

15.9

) 53

8.

1

(5.0

- 11

.2)

33

4.6

(3

.0 -

6.2)

19

3.

9 (2

.4 -

5.4)

79

12

.6

(7.9

- 17

.3)

63

10.2

(6

.7 -

13.8

) 75

12

.5

(9.6

- 15

.4)

56

9.7

(7

.4 -

11.9

)

Unc

orre

cted

dist

ance

refr

activ

e er

ror

38

55.9

31

58

.5

26

78.8

18

94

.7

44

55.7

42

66

.7

40

53.3

45

80

.4

Unc

orre

cted

nea

r ref

ract

ive

erro

r 34

4 64

.3

477

72.6

67

1 93

.6

474

97.1

46

9 74

.8

531

86.3

42

2 70

.5

438

75.5

46

Appendix 2 – Project Contributors

Steering Committee Members Dr Anthea Burnett Principal investigator, Research Manager at Brien Holden Vision

Institute Mr Drew Keys Regional Program Manager (Western Pacific) at the International

Agency for the Prevention of Blindness. Formerly, Project Manager (Papua New Guinea) at Brien Holden Vision Institute, General Manager at PNG Eye Care

Ms Mitasha Yu Regional Director Asia-Pacific at Brien Holden Vision Institute Dr Ling Lee Research Officer at Brien Holden Vision Institute Dr Jambi Garap Ophthalmologist, Board President, PNG Eye Care and President

of National Prevention of Blindness Committee PNG Dr Geoffrey Wabulembo

Paediatric Ophthalmologist, University of Papua New Guinea and CBM

Mr Samuel Koim Senior Manager at PNG Eye Care Dr Fabrizio D’Esposito Research Advisor at Fred Hollows Foundation Australia Ms Marleen Nelisse Program Director at Fred Hollows Foundation New Zealand Ms Grace Johnstone Data, Information and Research Coordinator at Fred Hollows

Foundation New Zealand

Management and data collection teams: Dr Anthea Burnett Principal investigator, Senior Research Officer at Brien Holden

Vision Institute Mr Drew Keys Regional Program Manager (Western Pacific) at the International

Agency for the Prevention of Blindness. Formerly, Project Manager Papua New Guinea at Brien Holden Vision Institute, General Manager at PNG Eye Care

Dr Ling Lee Research Officer at Brien Holden Vision Institute Dr Jambi Garap Ophthalmologist, Board President, PNG Eye Care and President

of National Prevention of Blindness Committee PNG Dr Geoffrey Wabulembo

Paediatric ophthalmologist, University of Papua New Guinea and CBM

Mr Samuel Koim Senior Manager at PNG Eye Care Dr Apisai Kerek Ophthalmologist at Port Moresby General Hospital, NCD Dr Robert Ko Ophthalmologist at Port Moresby General Hospital, NCD Dr David Pahau Ophthalmologist at Boram Hospital, Wewak, East Sepik Dr Waimbe Wahamu Ophthalmologist at Mt Hagen Hospital, Western Highlands Ms Theresa Gende Health Extension Officer at National Department of Health and

Lecturer at Divine Word University Mr Russell Kama Student investigator at University of PNG Mr Bartholomew Kapakeu

Student investigator at University of PNG

Ms Appolonia Parihuasi

Student investigator at University of PNG

Mr Ishmael Robert Student investigator at University of PNG

47

Mr Kua Yarawo Student investigator at University of PNG Mr Chris Paison Ophthalmic clinician at Alotau Provincial Hospital Ms Stephanie Koriapi Health Extension Officer at Boram General Hospital Mr Loamin Ikilik Nurse at Nonga General Hospital Ms Anita John Refractionist at PNG Eye Care Mr Jonah Jerry Eye Nursing Officer at Port Moresby General Hospital Ms Alison Poffley Research Assistant at Brien Holden Vision Institute

48

Appendix 3 – Randomly Selected Clusters

RANDOMLY SELECTED POPULATION UNITS IN SURVEY AREA – COASTAL REGION Cluster No.

Code Name of population unit Population

1 01010311401

Western Province Middle Fly District Gogodala Rural LLG Kawito Station Kawito Mission

150

2 01031221014

Western Province South Fly District Kiwai Rural LLG Maipani Maipani 773

3 02010509007

Gulf Province Kerema District Kotidanga Rural LLG Anea Tamdekengo 514

4 03010205047

Central Province Abau District Aroma Rural LLG Waro/Iruone Waro 137

5 03030715011

Central Province Kairuku - Hiri District Hiri Rural LLG Vanapa Kanobada No. 1

128

6 03041213026

Central Province Rigo District Rigo Coastal Rural LLG Gemo Gemo 792

7 06010314030

Northern (Oro) Province Ijivitari District Afore Rural LLG Ufia Umuwate

152

8 12010480004

Morobe Province Bulolo District Wau/Bulolo Urban LLG Bulolo Urban Klinkii Drive

132

9 12051682105

Morobe Province Lae District Lae Urban LLG Lae City Erema Street 706

10 12010501404

Morobe Province Bulolo District Wau Rural LLG Maus Bokis Tin Biscuit Settlement

295

11 12031006025

Morobe Province Huon District Salamaua Rural LLG Mubo Muekup 35

12* 12061704005

Morobe Province Markham District Onga/Waffa Rural LLG Siaga Siaga Warungao

310

13* 12073002002

Morobe Province Menyamya District Kapao Rural LLG Langamar Tuwatatila

143

14* 12092702021

Morobe Province Tawae/Siassi District Siassi Rural LLG Masele Masele 395

15 13010303008

Madang Province Bogia District Yawar Rural LLG Boroi Gabun 341

16 13020608401

Madang Province Madang District Transgogol Rural LLG Buroa Lagogen C/Sch

45

17 13041104026

Madang Province Rai Coast District Naho Rawa Rural LLG Boro Moguta

208

18 13051331410

Madang Province Sumkar District Karkar Rural LLG Bujon/Kurumtaur Kuburne Comm. Sch.

37

19 14041783630

East Sepik Province Wewak District Wewak Rural LLG Wewak Town Saure 2

398

20 14020510014

East Sepik Province Angoram District Angoram/Middle Sepik LLG Moim Moim

1,012

21 14031104025

East Sepik Province Maprik District Bumbita/Muhian Rural LLG Salata Salata

437

22 14051909009

East Sepik Province Wosera Gawi District Burui/Kunai Rural LLG Kwimba Nangutimbit

386

49

23 14062610006

East Sepik Province Yangoru Saussia District West Yangoru Rural LLG Bukitu Walgai

182

24 15020513001

West Sepik (Sandaun) Province Nuku District Mawase Rural LLG Abigu Abigu

366

25 15041301401

West Sepik (Sandaun) Province Vanimo/Green River District Bewani/Wutung Onei Rural LLG Wutung

76

RANDOMLY SELECTED POPULATION UNITS IN SURVEY AREA – HIGHALNDS REGION

Cluster No.

Code Name of population unit Population

1 07020611012

Southern Highlands Province Imbonggu District Imbongu Rural LLG Piambil 1 Inaipe

683

2 07033245013

Southern Highlands Province Kagua/Erave District Aiya Rural LLG Ripu/Maguta Omborama

78

3 07062110001

Southern Highlands Province Mendi/Munihu District Upper Mendi Rural LLG Birop 2 Birop 2

1,630

4 07072531003

Southern Highlands Province Nipa/Kutubu District Nipa Rural LLG Pulim 3 Minjakom

190

5 08010206401

Enga Province Kandep District Wage Rural LLG Porokale Potokale Sch 24

6 08030624009

Enga Province Lagaip/Pogera District Lagaip Rural LLG Yomondi Yomondi

798

7 08031516003

Enga Province Lagaip/Pogera District Pilikambi Rural LLG Kanak Wanepop (Wanepap)

678

8 08051330005

Enga Province Wapenamanda District Wapenamanda Rural LLG Unda Aiakalis

817

9 09020329001

Western Highlands Province Dei District Dei Rural LLG Kindal Kindal 536

10 09030437014

Western Highlands Province Mt Hagen District Mt Hagen Rural LLG Kugl Kulg

444

11 09071234001

Western Highlands Province Tambul/Nebilyer District Mt Giluwe Rural LLG Alkena 1 Purunupul

277

12 10020411002

Chimbu (Simbu) Province Gumine District Bomai/Gumai Rural LLG Kawaleku Boromil

649

13 10041007005

Chimbu (Simbu) Province Kerowagi District Gena/Waugla Rural LLG Dimbinyaundo Dibindiyaudo

272

14 10051601002

Chimbu (Simbu) Province Kundiawa/Gembogl District Waiye LLG Kupau Ombondo

305

15 11010101026

Eastern Highlands Province Daulo District Watabung Rural LLG Mangiro Monoga

24

16 11021404005

Eastern Highlands Province Goroka District Mimanalo Rural LLG Kabiufa No.2 Alinipayufa

532

17 11041706023

Eastern Highlands Province Kainanatu District Kamano No. 1 Rural LLG Bush Kamano Bara-Onofi

1,275

18 11052101072

Eastern Highlands Province Lufa District Yagaria Rural LLG Higivavi Bopa No 2

124

19 11072204035

Eastern Highlands Province Okapa District West Okapa Rural LLG Tarabo Ketaga

159

20 21041111006

Hela Province Komo/Magarima District Hulia Rural LLG Hol'la Homa 868

50

21 21051517022

Hela Province Koroba/Kopiago District Lake Kopiago Rural LLG Wanakipi Wane 1

130

22* 22010282005

Jiwaka Province Anglimp/South Waghi District South Waghi Rural LLG Minj Urban DPI Compound

65

23 22010203401

Jiwaka Province Anglimp/South Waghi District South Waghi Rural LLG Aviamp 2 Nazarene Cir.

24

24 22040631007

Jiwaka Province Jimi District Jimi Rural LLG Korenju Borgol 506

25 22061521025

Jiwaka Province North Waghi District Nondugl Rural LLG Onil 1 Konskan Nol Egel

404

RANDOMLY SELECTED POPULATION UNITS IN SURVEY AREA – ISLANDS REGION

Cluster No.

Code Name of population unit Population

1 05010585013

Milne Bay Province Alotau District Huhu Rural LLG Hagita Estate Hagita Nursery

426

2 05010501009

Milne Bay Province Alotau District Huhu Rural LLG Mutu'uwa Mutuyuwa

778

3 05020901008

Milne Bay Province Samarai-Murua District Louisiade Rural LLG Mwabua Gelagela

110

4 05031209029

Milne Bay Province Kiriwina-Goodenough District Kiriwina Rural LLG Okaikoda Walesi

273

5 05041401009

Milne Bay Province Esa'ala District West Ferguson Rural LLG Fayayana Asagamwana

279

6 16010680002

Manus Province Manus District Lorengau Urban LLG Lorengau Urban Manus High School

466

7 16011109002

Manus Province Manus District Balopa LLG Lako Lako 182

8 17010302033

New Ireland Province Kavieng District Tikana Rural LLG Nonovaul Limanak/Usen

335

9 17020514023

New Ireland Province Namatanai District Namatanai Rural LLG Sopau Sopau

308

10 17020802009

New Ireland Province Namatanai District Tanir Rural LLG Fonli Fonli 634

11 18010104002

East New Britain Province Gazelle District Central Gazelle Rural LLG Napapar No. 4 Napapar No.4 Vill

1,051

12 18010315023

East New Britain Province Gazelle District Lassul Baining Rural LLG Komgi Komgi

422

13 18010521506

East New Britain Province Gazelle District Vunadidir/Toma Rural LLG Wariki No.3 Oisca

57

14 18020804003

East New Britain Province Kokopo District Kokopo/Vunamami Urban LLG Vunabalbal Vunabalbal

819

15 18031029041

East New Britain Province Pomio District Central/Inland Pomio LLG Marmu Pelly

99

16 18041501401

East New Britain Province Rabaul District Balanataman Rural LLG Ratung Ratung Asing Settlmnt

128

17 19020980056

West New Britain Province Talasea District Kimbe Urban LLG Kimbe Urban Sect. 83

456

18 19010407018

West New Britain Province Kandrian/Gloucester District Kandrian Inland Rural LLG Awon Lapalam

222

51

19 19020610028

West New Britain Province Talasea District Bialla Rural LLG Bialla Waigo Vop

117

20 19020804006

West New Britain Province Talasea District Hoskins Rural LLG Kalu Gavaiva

1,188

21 19021101402

West New Britain Province Talasea District Talasea Rural LLG Nalabu Huveni / Lobe

1,072

22 20010203007

Autonomous Region of Bougainville North Bougainville District Kunua LLG Rapois Kopaei

349

23 20010405009

Autonomous Region of Bougainville North Bougainville District Buka LLG Halia Tohatsi

1,462

24 20020806001

Autonomous Region of Bougainville Central Bougainville District Arawa LLG Avaipa Siuema

559

25 20030905008

Autonomous Region of Bougainville South Bougainville District Buin LLG Lenoke Oremutsi

289

RANDOMLY SELECTED POPULATION UNITS IN SURVEY AREA – NATIONAL CAPITAL DISTRICT

Cluster No.

Code Name of population unit Population

1 04010180014

National Capital District National Capital District National Capital District Gerehu Urban Maika Str

857

2 04010180036

National Capital District National Capital District National Capital District Gerehu Urban Toliman C

532

3 04010180059

National Capital District National Capital District National Capital District Gerehu Urban Rainbow 5

526

4 04010181014

National Capital District National Capital District National Capital District Waigani/University Ono

629

5 04010181041

National Capital District National Capital District National Capital District Waigani/University For

519

6 04010182002

National Capital District National Capital District National Capital District Tokarara/Hohola Urban

2,181

7 04010182021

National Capital District National Capital District National Capital District Tokarara/Hohola Urban

767

8 04010182040

National Capital District National Capital District National Capital District Tokarara/Hohola Urban

428

9 04010182060

National Capital District National Capital District National Capital District Tokarara/Hohola Urban

612

10 04010183020

National Capital District National Capital District National Capital District Gordons/Saraga Urban D

439

11 04010183043

National Capital District National Capital District National Capital District Gordons/Saraga Urban H

303

12 04010183056

National Capital District National Capital District National Capital District Gordons/Saraga Urban G

218

13 04010184010

National Capital District National Capital District National Capital District Boroko / Korobosea Urb

317

14 04010184049

National Capital District National Capital District National Capital District Boroko / Korobosea Urb

210

15 04010184075

National Capital District National Capital District National Capital District Boroko / Korobosea Urb

3,073

16 04010185003

National Capital District National Capital District National Capital District Kilakila / Kaugere Urb

1,187

52

17 04010185022

National Capital District National Capital District National Capital District Kilakila / Kaugere Urb

539

18 04010185039

National Capital District National Capital District National Capital District Kilakila / Kaugere Urb

950

19 04010186003

National Capital District National Capital District National Capital District Town / Hanuabada Urban

1,162

20 04010186030

National Capital District National Capital District National Capital District Town / Hanuabada Urban

2,035

21 04010186039

National Capital District National Capital District National Capital District Town / Hanuabada Urban

2,039

22 04010187505

National Capital District National Capital District National Capital District Laloki / Napanapa Urba

384

23 04010188402

National Capital District National Capital District National Capital District Bomana Urban Bomana Tr

46

24 04010188414

National Capital District National Capital District National Capital District Bomana Urban Kobaena

252

25 04010188524

National Capital District National Capital District National Capital District Bomana Urban Popondett

2,386

* Clusters were not accessible – the nearest closest geographical census unit was selected instead.

53

Appendix 4 – Regional Reports

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70